In [ ]:
import os
In [ ]:
from google.colab import drive
drive.mount('/content/gdrive')

Drive already mounted at /content/gdrive; to attempt to forcibly remount, call drive.mount("/content/gdrive", force_remount=True).
In [ ]:
from google.colab import auth
auth.authenticate_user()
In [ ]:
folder_path = '/content/gdrive/MyDrive/DLS/HW2/'
os.chdir(folder_path)
In [ ]:
!pip install librosa

Requirement already satisfied: librosa in /usr/local/lib/python3.10/dist-packages (0.10.1)
Requirement already satisfied: audioread>=2.1.9 in /usr/local/lib/python3.10/dist-packages (from librosa) (3.0.1)
Requirement already satisfied: numpy!=1.22.0,!=1.22.1,!=1.22.2,>=1.20.3 in /usr/local/lib/python3.10/dist-packages (from librosa) (1.23.5)
Requirement already satisfied: scipy>=1.2.0 in /usr/local/lib/python3.10/dist-packages (from librosa) (1.11.3)
Requirement already satisfied: scikit-learn>=0.20.0 in /usr/local/lib/python3.10/dist-packages (from librosa) (1.2.2)
Requirement already satisfied: joblib>=0.14 in /usr/local/lib/python3.10/dist-packages (from librosa) (1.3.2)
Requirement already satisfied: decorator>=4.3.0 in /usr/local/lib/python3.10/dist-packages (from librosa) (4.4.2)
Requirement already satisfied: numba>=0.51.0 in /usr/local/lib/python3.10/dist-packages (from librosa) (0.56.4)
Requirement already satisfied: soundfile>=0.12.1 in /usr/local/lib/python3.10/dist-packages (from librosa) (0.12.1)
Requirement already satisfied: pooch>=1.0 in /usr/local/lib/python3.10/dist-packages (from librosa) (1.7.0)
Requirement already satisfied: soxr>=0.3.2 in /usr/local/lib/python3.10/dist-packages (from librosa) (0.3.7)
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Requirement already satisfied: lazy-loader>=0.1 in /usr/local/lib/python3.10/dist-packages (from librosa) (0.3)
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Requirement already satisfied: threadpoolctl>=2.0.0 in /usr/local/lib/python3.10/dist-packages (from scikit-learn>=0.20.0->librosa) (3.2.0)
Requirement already satisfied: cffi>=1.0 in /usr/local/lib/python3.10/dist-packages (from soundfile>=0.12.1->librosa) (1.16.0)
Requirement already satisfied: pycparser in /usr/local/lib/python3.10/dist-packages (from cffi>=1.0->soundfile>=0.12.1->librosa) (2.21)
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Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests>=2.19.0->pooch>=1.0->librosa) (2023.7.22)
In [ ]:
#libraries
import librosa
import soundfile as sf
import numpy as np
import tensorflow as tf
import matplotlib.pyplot as plt

Q1.

In [ ]:
#plot of clean audio signal
s, sr=librosa.load('data/train_clean_male.wav', sr=None)
fig, ax = plt.subplots(nrows=1, sharex=True)
librosa.display.waveshow(s, sr=sr, ax=ax)
Out[ ]:
<librosa.display.AdaptiveWaveplot at 0x7cc5fd82beb0>
In [ ]:
#plot of noisy audio signal
sn, sr=librosa.load('data/train_dirty_male.wav', sr=None)
fig, ax = plt.subplots(nrows=1, sharex=True)
librosa.display.waveshow(sn, sr=sr, ax=ax)
Out[ ]:
<librosa.display.AdaptiveWaveplot at 0x7cc5f311e4d0>
In [ ]:
#calculate stft of the signals
s, sr=librosa.load('data/train_clean_male.wav', sr=None)
S=librosa.stft(s, n_fft=1024, hop_length=512)
sn, sr=librosa.load('data/train_dirty_male.wav', sr=None)
X=librosa.stft(sn, n_fft=1024, hop_length=512)
In [ ]:
S.shape
X.shape
Out[ ]:
(513, 2459)
In [ ]:
#magnitude of clean and noisy signals
S_mag = np.abs(S).T
X_mag = np.abs(X).T
In [ ]:
#deep neural network where input vector is column vector of 513 dim of X noisy signal
#and output vector is corresponding vector of S clean audio signal.

initializer = tf.keras.initializers.HeNormal()
model = tf.keras.Sequential([
    tf.keras.layers.InputLayer(input_shape = X_mag.shape[1]),
    tf.keras.layers.Dense(513 , activation = 'leaky_relu'),
    tf.keras.layers.Dense(513, activation = 'leaky_relu'),
    tf.keras.layers.Dense(units = S_mag.shape[1], activation = 'relu')
])

experiments: no early stopping

  1. epochs = 50 , batch size = 32 , snr = 6 , hidden: relu , He
  2. epochs = 100, batch size = 16, snr = 4.96, hidden: relu , He
  3. epochs = 50, batch size = 32, snr = 8.83, hidden: leaky relu , He
  4. epochs = 50, batch size = 128, snr = 9.03, hidden: leaky relu , He
  5. epochs = 100, batch size = 128, snr = -1.9, hidden: leaky relu , He
  6. epochs = 200, batch size = 32, snr = 9.25, hidden : leaky relu , He; loss 0.028
  7. epochs = 200, batch_size = 32, snr = 4.28, hidden : relu, He.
  8. epochs = 200, batch_size = 32 , snr = 6. hidden : relu, 513 - kind of better than others.
  9. epochs = 200, batch_size = 32 , snr = 9. hidden : leaky-relu, 513
  10. epochs = 200, batch_size = 32 , snr =5 hidden : relu, 513-3
In [ ]:
#train network
model.compile(optimizer = 'Adam', loss = 'mse', metrics = ['accuracy'])
history = model.fit(X_mag , S_mag, epochs = 200 , batch_size = 32, validation_split = 0.2, shuffle = True)

Epoch 1/200
62/62 [==============================] - 2s 7ms/step - loss: 0.0405 - accuracy: 0.1871 - val_loss: 0.0280 - val_accuracy: 0.2764
Epoch 2/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0171 - accuracy: 0.3620 - val_loss: 0.0194 - val_accuracy: 0.3394
Epoch 3/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0121 - accuracy: 0.3965 - val_loss: 0.0153 - val_accuracy: 0.3476
Epoch 4/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0088 - accuracy: 0.4296 - val_loss: 0.0135 - val_accuracy: 0.4126
Epoch 5/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0077 - accuracy: 0.4387 - val_loss: 0.0128 - val_accuracy: 0.4106
Epoch 6/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0070 - accuracy: 0.4448 - val_loss: 0.0123 - val_accuracy: 0.4146
Epoch 7/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0066 - accuracy: 0.4565 - val_loss: 0.0124 - val_accuracy: 0.3984
Epoch 8/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0068 - accuracy: 0.4540 - val_loss: 0.0118 - val_accuracy: 0.4146
Epoch 9/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0070 - accuracy: 0.4494 - val_loss: 0.0126 - val_accuracy: 0.3963
Epoch 10/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0068 - accuracy: 0.4570 - val_loss: 0.0125 - val_accuracy: 0.3882
Epoch 11/200
62/62 [==============================] - 0s 3ms/step - loss: 0.0068 - accuracy: 0.4550 - val_loss: 0.0112 - val_accuracy: 0.4228
Epoch 12/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0057 - accuracy: 0.4733 - val_loss: 0.0113 - val_accuracy: 0.4146
Epoch 13/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0051 - accuracy: 0.4753 - val_loss: 0.0108 - val_accuracy: 0.4431
Epoch 14/200
62/62 [==============================] - 0s 3ms/step - loss: 0.0049 - accuracy: 0.4804 - val_loss: 0.0103 - val_accuracy: 0.4207
Epoch 15/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0050 - accuracy: 0.4830 - val_loss: 0.0103 - val_accuracy: 0.4329
Epoch 16/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0049 - accuracy: 0.4850 - val_loss: 0.0104 - val_accuracy: 0.4248
Epoch 17/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0044 - accuracy: 0.4901 - val_loss: 0.0101 - val_accuracy: 0.4309
Epoch 18/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0051 - accuracy: 0.4870 - val_loss: 0.0102 - val_accuracy: 0.4146
Epoch 19/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0051 - accuracy: 0.4860 - val_loss: 0.0099 - val_accuracy: 0.4268
Epoch 20/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0047 - accuracy: 0.4911 - val_loss: 0.0096 - val_accuracy: 0.4248
Epoch 21/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0047 - accuracy: 0.4865 - val_loss: 0.0106 - val_accuracy: 0.4228
Epoch 22/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0046 - accuracy: 0.4972 - val_loss: 0.0112 - val_accuracy: 0.4248
Epoch 23/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0050 - accuracy: 0.4870 - val_loss: 0.0096 - val_accuracy: 0.4329
Epoch 24/200
62/62 [==============================] - 0s 5ms/step - loss: 0.0042 - accuracy: 0.5064 - val_loss: 0.0095 - val_accuracy: 0.4268
Epoch 25/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0045 - accuracy: 0.4962 - val_loss: 0.0091 - val_accuracy: 0.4350
Epoch 26/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0040 - accuracy: 0.5018 - val_loss: 0.0090 - val_accuracy: 0.4289
Epoch 27/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0040 - accuracy: 0.5099 - val_loss: 0.0092 - val_accuracy: 0.4268
Epoch 28/200
62/62 [==============================] - 0s 3ms/step - loss: 0.0043 - accuracy: 0.4997 - val_loss: 0.0091 - val_accuracy: 0.4309
Epoch 29/200
62/62 [==============================] - 0s 3ms/step - loss: 0.0040 - accuracy: 0.5018 - val_loss: 0.0092 - val_accuracy: 0.4289
Epoch 30/200
62/62 [==============================] - 0s 3ms/step - loss: 0.0036 - accuracy: 0.5140 - val_loss: 0.0092 - val_accuracy: 0.4268
Epoch 31/200
62/62 [==============================] - 0s 3ms/step - loss: 0.0038 - accuracy: 0.5074 - val_loss: 0.0086 - val_accuracy: 0.4248
Epoch 32/200
62/62 [==============================] - 0s 3ms/step - loss: 0.0042 - accuracy: 0.5201 - val_loss: 0.0090 - val_accuracy: 0.4187
Epoch 33/200
62/62 [==============================] - 0s 3ms/step - loss: 0.0039 - accuracy: 0.5150 - val_loss: 0.0094 - val_accuracy: 0.4370
Epoch 34/200
62/62 [==============================] - 0s 3ms/step - loss: 0.0041 - accuracy: 0.5145 - val_loss: 0.0101 - val_accuracy: 0.4350
Epoch 35/200
62/62 [==============================] - 0s 3ms/step - loss: 0.0040 - accuracy: 0.5236 - val_loss: 0.0090 - val_accuracy: 0.4309
Epoch 36/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0037 - accuracy: 0.5247 - val_loss: 0.0084 - val_accuracy: 0.4289
Epoch 37/200
62/62 [==============================] - 0s 3ms/step - loss: 0.0036 - accuracy: 0.5241 - val_loss: 0.0084 - val_accuracy: 0.4126
Epoch 38/200
62/62 [==============================] - 0s 3ms/step - loss: 0.0033 - accuracy: 0.5257 - val_loss: 0.0088 - val_accuracy: 0.4187
Epoch 39/200
62/62 [==============================] - 0s 3ms/step - loss: 0.0034 - accuracy: 0.5323 - val_loss: 0.0087 - val_accuracy: 0.4329
Epoch 40/200
62/62 [==============================] - 0s 3ms/step - loss: 0.0034 - accuracy: 0.5358 - val_loss: 0.0099 - val_accuracy: 0.4289
Epoch 41/200
62/62 [==============================] - 0s 3ms/step - loss: 0.0041 - accuracy: 0.5170 - val_loss: 0.0083 - val_accuracy: 0.4329
Epoch 42/200
62/62 [==============================] - 0s 3ms/step - loss: 0.0032 - accuracy: 0.5267 - val_loss: 0.0089 - val_accuracy: 0.4370
Epoch 43/200
62/62 [==============================] - 0s 3ms/step - loss: 0.0032 - accuracy: 0.5257 - val_loss: 0.0082 - val_accuracy: 0.4268
Epoch 44/200
62/62 [==============================] - 0s 3ms/step - loss: 0.0029 - accuracy: 0.5399 - val_loss: 0.0081 - val_accuracy: 0.4553
Epoch 45/200
62/62 [==============================] - 0s 3ms/step - loss: 0.0033 - accuracy: 0.5282 - val_loss: 0.0086 - val_accuracy: 0.4370
Epoch 46/200
62/62 [==============================] - 0s 3ms/step - loss: 0.0037 - accuracy: 0.5318 - val_loss: 0.0082 - val_accuracy: 0.4675
Epoch 47/200
62/62 [==============================] - 0s 3ms/step - loss: 0.0036 - accuracy: 0.5328 - val_loss: 0.0091 - val_accuracy: 0.4573
Epoch 48/200
62/62 [==============================] - 0s 3ms/step - loss: 0.0035 - accuracy: 0.5318 - val_loss: 0.0080 - val_accuracy: 0.4207
Epoch 49/200
62/62 [==============================] - 0s 3ms/step - loss: 0.0031 - accuracy: 0.5465 - val_loss: 0.0080 - val_accuracy: 0.4614
Epoch 50/200
62/62 [==============================] - 0s 3ms/step - loss: 0.0032 - accuracy: 0.5379 - val_loss: 0.0077 - val_accuracy: 0.4512
Epoch 51/200
62/62 [==============================] - 0s 3ms/step - loss: 0.0029 - accuracy: 0.5547 - val_loss: 0.0077 - val_accuracy: 0.4614
Epoch 52/200
62/62 [==============================] - 0s 3ms/step - loss: 0.0026 - accuracy: 0.5572 - val_loss: 0.0079 - val_accuracy: 0.4695
Epoch 53/200
62/62 [==============================] - 0s 3ms/step - loss: 0.0024 - accuracy: 0.5587 - val_loss: 0.0075 - val_accuracy: 0.4593
Epoch 54/200
62/62 [==============================] - 0s 3ms/step - loss: 0.0025 - accuracy: 0.5541 - val_loss: 0.0074 - val_accuracy: 0.4675
Epoch 55/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0027 - accuracy: 0.5557 - val_loss: 0.0077 - val_accuracy: 0.4634
Epoch 56/200
62/62 [==============================] - 0s 3ms/step - loss: 0.0031 - accuracy: 0.5496 - val_loss: 0.0077 - val_accuracy: 0.4451
Epoch 57/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0029 - accuracy: 0.5450 - val_loss: 0.0076 - val_accuracy: 0.4451
Epoch 58/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0027 - accuracy: 0.5531 - val_loss: 0.0079 - val_accuracy: 0.4654
Epoch 59/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0032 - accuracy: 0.5460 - val_loss: 0.0077 - val_accuracy: 0.4715
Epoch 60/200
62/62 [==============================] - 0s 3ms/step - loss: 0.0031 - accuracy: 0.5541 - val_loss: 0.0079 - val_accuracy: 0.4736
Epoch 61/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0037 - accuracy: 0.5572 - val_loss: 0.0085 - val_accuracy: 0.4492
Epoch 62/200
62/62 [==============================] - 0s 3ms/step - loss: 0.0037 - accuracy: 0.5363 - val_loss: 0.0087 - val_accuracy: 0.4472
Epoch 63/200
62/62 [==============================] - 0s 3ms/step - loss: 0.0043 - accuracy: 0.5292 - val_loss: 0.0091 - val_accuracy: 0.4614
Epoch 64/200
62/62 [==============================] - 0s 3ms/step - loss: 0.0039 - accuracy: 0.5297 - val_loss: 0.0091 - val_accuracy: 0.4492
Epoch 65/200
62/62 [==============================] - 0s 3ms/step - loss: 0.0044 - accuracy: 0.5363 - val_loss: 0.0081 - val_accuracy: 0.4431
Epoch 66/200
62/62 [==============================] - 0s 3ms/step - loss: 0.0059 - accuracy: 0.5221 - val_loss: 0.0098 - val_accuracy: 0.4167
Epoch 67/200
62/62 [==============================] - 0s 3ms/step - loss: 0.0051 - accuracy: 0.5165 - val_loss: 0.0087 - val_accuracy: 0.4411
Epoch 68/200
62/62 [==============================] - 0s 3ms/step - loss: 0.0044 - accuracy: 0.5282 - val_loss: 0.0086 - val_accuracy: 0.4553
Epoch 69/200
62/62 [==============================] - 0s 3ms/step - loss: 0.0033 - accuracy: 0.5414 - val_loss: 0.0080 - val_accuracy: 0.4715
Epoch 70/200
62/62 [==============================] - 0s 3ms/step - loss: 0.0028 - accuracy: 0.5552 - val_loss: 0.0083 - val_accuracy: 0.4492
Epoch 71/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0027 - accuracy: 0.5552 - val_loss: 0.0073 - val_accuracy: 0.4898
Epoch 72/200
62/62 [==============================] - 0s 3ms/step - loss: 0.0025 - accuracy: 0.5724 - val_loss: 0.0075 - val_accuracy: 0.4695
Epoch 73/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0023 - accuracy: 0.5684 - val_loss: 0.0072 - val_accuracy: 0.4898
Epoch 74/200
62/62 [==============================] - 0s 3ms/step - loss: 0.0024 - accuracy: 0.5816 - val_loss: 0.0070 - val_accuracy: 0.4654
Epoch 75/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0023 - accuracy: 0.5699 - val_loss: 0.0073 - val_accuracy: 0.4776
Epoch 76/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0025 - accuracy: 0.5679 - val_loss: 0.0074 - val_accuracy: 0.4634
Epoch 77/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0024 - accuracy: 0.5755 - val_loss: 0.0077 - val_accuracy: 0.4512
Epoch 78/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0023 - accuracy: 0.5801 - val_loss: 0.0071 - val_accuracy: 0.4837
Epoch 79/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0020 - accuracy: 0.5785 - val_loss: 0.0071 - val_accuracy: 0.4736
Epoch 80/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0019 - accuracy: 0.5902 - val_loss: 0.0068 - val_accuracy: 0.4898
Epoch 81/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0017 - accuracy: 0.5867 - val_loss: 0.0067 - val_accuracy: 0.4939
Epoch 82/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0018 - accuracy: 0.5913 - val_loss: 0.0068 - val_accuracy: 0.4817
Epoch 83/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0020 - accuracy: 0.5770 - val_loss: 0.0070 - val_accuracy: 0.4878
Epoch 84/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0021 - accuracy: 0.5780 - val_loss: 0.0071 - val_accuracy: 0.4533
Epoch 85/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0023 - accuracy: 0.5857 - val_loss: 0.0074 - val_accuracy: 0.4898
Epoch 86/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0025 - accuracy: 0.5735 - val_loss: 0.0073 - val_accuracy: 0.4756
Epoch 87/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0025 - accuracy: 0.5806 - val_loss: 0.0073 - val_accuracy: 0.4533
Epoch 88/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0029 - accuracy: 0.5582 - val_loss: 0.0096 - val_accuracy: 0.4593
Epoch 89/200
62/62 [==============================] - 0s 3ms/step - loss: 0.0036 - accuracy: 0.5435 - val_loss: 0.0087 - val_accuracy: 0.4634
Epoch 90/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0041 - accuracy: 0.5363 - val_loss: 0.0090 - val_accuracy: 0.4492
Epoch 91/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0036 - accuracy: 0.5470 - val_loss: 0.0085 - val_accuracy: 0.5000
Epoch 92/200
62/62 [==============================] - 0s 3ms/step - loss: 0.0035 - accuracy: 0.5526 - val_loss: 0.0075 - val_accuracy: 0.4431
Epoch 93/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0029 - accuracy: 0.5597 - val_loss: 0.0073 - val_accuracy: 0.4939
Epoch 94/200
62/62 [==============================] - 0s 3ms/step - loss: 0.0024 - accuracy: 0.5745 - val_loss: 0.0075 - val_accuracy: 0.4715
Epoch 95/200
62/62 [==============================] - 0s 3ms/step - loss: 0.0026 - accuracy: 0.5770 - val_loss: 0.0070 - val_accuracy: 0.4980
Epoch 96/200
62/62 [==============================] - 0s 3ms/step - loss: 0.0025 - accuracy: 0.5760 - val_loss: 0.0075 - val_accuracy: 0.4715
Epoch 97/200
62/62 [==============================] - 0s 3ms/step - loss: 0.0022 - accuracy: 0.5897 - val_loss: 0.0067 - val_accuracy: 0.4837
Epoch 98/200
62/62 [==============================] - 0s 3ms/step - loss: 0.0019 - accuracy: 0.6009 - val_loss: 0.0071 - val_accuracy: 0.5142
Epoch 99/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0019 - accuracy: 0.5963 - val_loss: 0.0067 - val_accuracy: 0.4675
Epoch 100/200
62/62 [==============================] - 0s 3ms/step - loss: 0.0019 - accuracy: 0.6004 - val_loss: 0.0071 - val_accuracy: 0.5061
Epoch 101/200
62/62 [==============================] - 0s 3ms/step - loss: 0.0020 - accuracy: 0.6065 - val_loss: 0.0070 - val_accuracy: 0.5061
Epoch 102/200
62/62 [==============================] - 0s 3ms/step - loss: 0.0018 - accuracy: 0.6009 - val_loss: 0.0068 - val_accuracy: 0.4797
Epoch 103/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0020 - accuracy: 0.5963 - val_loss: 0.0071 - val_accuracy: 0.4817
Epoch 104/200
62/62 [==============================] - 0s 3ms/step - loss: 0.0021 - accuracy: 0.5968 - val_loss: 0.0071 - val_accuracy: 0.4756
Epoch 105/200
62/62 [==============================] - 0s 3ms/step - loss: 0.0023 - accuracy: 0.5699 - val_loss: 0.0072 - val_accuracy: 0.4776
Epoch 106/200
62/62 [==============================] - 0s 3ms/step - loss: 0.0025 - accuracy: 0.5806 - val_loss: 0.0069 - val_accuracy: 0.4898
Epoch 107/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0021 - accuracy: 0.5948 - val_loss: 0.0072 - val_accuracy: 0.5061
Epoch 108/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0020 - accuracy: 0.5867 - val_loss: 0.0070 - val_accuracy: 0.5000
Epoch 109/200
62/62 [==============================] - 0s 3ms/step - loss: 0.0021 - accuracy: 0.6055 - val_loss: 0.0073 - val_accuracy: 0.4593
Epoch 110/200
62/62 [==============================] - 0s 3ms/step - loss: 0.0022 - accuracy: 0.5918 - val_loss: 0.0069 - val_accuracy: 0.4959
Epoch 111/200
62/62 [==============================] - 0s 3ms/step - loss: 0.0023 - accuracy: 0.5821 - val_loss: 0.0077 - val_accuracy: 0.4980
Epoch 112/200
62/62 [==============================] - 0s 3ms/step - loss: 0.0030 - accuracy: 0.5750 - val_loss: 0.0078 - val_accuracy: 0.4736
Epoch 113/200
62/62 [==============================] - 0s 3ms/step - loss: 0.0036 - accuracy: 0.5623 - val_loss: 0.0085 - val_accuracy: 0.5102
Epoch 114/200
62/62 [==============================] - 0s 3ms/step - loss: 0.0030 - accuracy: 0.5684 - val_loss: 0.0079 - val_accuracy: 0.4573
Epoch 115/200
62/62 [==============================] - 0s 3ms/step - loss: 0.0025 - accuracy: 0.5826 - val_loss: 0.0075 - val_accuracy: 0.4614
Epoch 116/200
62/62 [==============================] - 0s 3ms/step - loss: 0.0023 - accuracy: 0.5877 - val_loss: 0.0073 - val_accuracy: 0.5000
Epoch 117/200
62/62 [==============================] - 0s 3ms/step - loss: 0.0021 - accuracy: 0.6019 - val_loss: 0.0070 - val_accuracy: 0.5000
Epoch 118/200
62/62 [==============================] - 0s 3ms/step - loss: 0.0020 - accuracy: 0.6085 - val_loss: 0.0070 - val_accuracy: 0.4878
Epoch 119/200
62/62 [==============================] - 0s 3ms/step - loss: 0.0020 - accuracy: 0.5979 - val_loss: 0.0073 - val_accuracy: 0.4492
Epoch 120/200
62/62 [==============================] - 0s 3ms/step - loss: 0.0018 - accuracy: 0.5943 - val_loss: 0.0068 - val_accuracy: 0.4959
Epoch 121/200
62/62 [==============================] - 0s 3ms/step - loss: 0.0018 - accuracy: 0.6035 - val_loss: 0.0067 - val_accuracy: 0.5122
Epoch 122/200
62/62 [==============================] - 0s 3ms/step - loss: 0.0018 - accuracy: 0.6106 - val_loss: 0.0066 - val_accuracy: 0.4837
Epoch 123/200
62/62 [==============================] - 0s 3ms/step - loss: 0.0017 - accuracy: 0.6167 - val_loss: 0.0070 - val_accuracy: 0.4919
Epoch 124/200
62/62 [==============================] - 0s 3ms/step - loss: 0.0016 - accuracy: 0.6126 - val_loss: 0.0071 - val_accuracy: 0.4776
Epoch 125/200
62/62 [==============================] - 0s 3ms/step - loss: 0.0016 - accuracy: 0.6121 - val_loss: 0.0073 - val_accuracy: 0.5102
Epoch 126/200
62/62 [==============================] - 0s 3ms/step - loss: 0.0020 - accuracy: 0.6029 - val_loss: 0.0069 - val_accuracy: 0.4898
Epoch 127/200
62/62 [==============================] - 0s 3ms/step - loss: 0.0018 - accuracy: 0.6055 - val_loss: 0.0071 - val_accuracy: 0.4817
Epoch 128/200
62/62 [==============================] - 0s 3ms/step - loss: 0.0019 - accuracy: 0.6019 - val_loss: 0.0079 - val_accuracy: 0.4837
Epoch 129/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0021 - accuracy: 0.5968 - val_loss: 0.0073 - val_accuracy: 0.4919
Epoch 130/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0022 - accuracy: 0.6029 - val_loss: 0.0077 - val_accuracy: 0.4878
Epoch 131/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0023 - accuracy: 0.5943 - val_loss: 0.0071 - val_accuracy: 0.5000
Epoch 132/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0024 - accuracy: 0.6029 - val_loss: 0.0074 - val_accuracy: 0.5102
Epoch 133/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0023 - accuracy: 0.5979 - val_loss: 0.0072 - val_accuracy: 0.4837
Epoch 134/200
62/62 [==============================] - 0s 3ms/step - loss: 0.0021 - accuracy: 0.5943 - val_loss: 0.0072 - val_accuracy: 0.5102
Epoch 135/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0023 - accuracy: 0.5989 - val_loss: 0.0078 - val_accuracy: 0.4898
Epoch 136/200
62/62 [==============================] - 0s 3ms/step - loss: 0.0023 - accuracy: 0.5963 - val_loss: 0.0075 - val_accuracy: 0.4756
Epoch 137/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0024 - accuracy: 0.5913 - val_loss: 0.0073 - val_accuracy: 0.4939
Epoch 138/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0022 - accuracy: 0.6004 - val_loss: 0.0074 - val_accuracy: 0.5122
Epoch 139/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0021 - accuracy: 0.6070 - val_loss: 0.0069 - val_accuracy: 0.4736
Epoch 140/200
62/62 [==============================] - 0s 3ms/step - loss: 0.0020 - accuracy: 0.6060 - val_loss: 0.0073 - val_accuracy: 0.4959
Epoch 141/200
62/62 [==============================] - 0s 3ms/step - loss: 0.0019 - accuracy: 0.6157 - val_loss: 0.0068 - val_accuracy: 0.5163
Epoch 142/200
62/62 [==============================] - 0s 3ms/step - loss: 0.0019 - accuracy: 0.6080 - val_loss: 0.0070 - val_accuracy: 0.4878
Epoch 143/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0017 - accuracy: 0.5877 - val_loss: 0.0069 - val_accuracy: 0.5020
Epoch 144/200
62/62 [==============================] - 0s 3ms/step - loss: 0.0018 - accuracy: 0.6131 - val_loss: 0.0069 - val_accuracy: 0.5142
Epoch 145/200
62/62 [==============================] - 0s 3ms/step - loss: 0.0017 - accuracy: 0.6274 - val_loss: 0.0074 - val_accuracy: 0.5081
Epoch 146/200
62/62 [==============================] - 0s 3ms/step - loss: 0.0022 - accuracy: 0.6136 - val_loss: 0.0070 - val_accuracy: 0.4837
Epoch 147/200
62/62 [==============================] - 0s 3ms/step - loss: 0.0024 - accuracy: 0.6040 - val_loss: 0.0075 - val_accuracy: 0.4654
Epoch 148/200
62/62 [==============================] - 0s 3ms/step - loss: 0.0022 - accuracy: 0.6024 - val_loss: 0.0071 - val_accuracy: 0.5041
Epoch 149/200
62/62 [==============================] - 0s 3ms/step - loss: 0.0027 - accuracy: 0.5958 - val_loss: 0.0074 - val_accuracy: 0.4980
Epoch 150/200
62/62 [==============================] - 0s 3ms/step - loss: 0.0022 - accuracy: 0.6004 - val_loss: 0.0072 - val_accuracy: 0.4878
Epoch 151/200
62/62 [==============================] - 0s 3ms/step - loss: 0.0022 - accuracy: 0.6096 - val_loss: 0.0077 - val_accuracy: 0.5020
Epoch 152/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0022 - accuracy: 0.6121 - val_loss: 0.0070 - val_accuracy: 0.4919
Epoch 153/200
62/62 [==============================] - 0s 3ms/step - loss: 0.0018 - accuracy: 0.6202 - val_loss: 0.0073 - val_accuracy: 0.5020
Epoch 154/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0022 - accuracy: 0.6055 - val_loss: 0.0071 - val_accuracy: 0.4939
Epoch 155/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0020 - accuracy: 0.6233 - val_loss: 0.0074 - val_accuracy: 0.4634
Epoch 156/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0019 - accuracy: 0.6060 - val_loss: 0.0068 - val_accuracy: 0.4980
Epoch 157/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0017 - accuracy: 0.6167 - val_loss: 0.0068 - val_accuracy: 0.4837
Epoch 158/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0017 - accuracy: 0.6243 - val_loss: 0.0069 - val_accuracy: 0.5122
Epoch 159/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0016 - accuracy: 0.6299 - val_loss: 0.0067 - val_accuracy: 0.5102
Epoch 160/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0015 - accuracy: 0.6253 - val_loss: 0.0068 - val_accuracy: 0.4939
Epoch 161/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0016 - accuracy: 0.6218 - val_loss: 0.0066 - val_accuracy: 0.5305
Epoch 162/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0014 - accuracy: 0.6329 - val_loss: 0.0069 - val_accuracy: 0.4919
Epoch 163/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0015 - accuracy: 0.6294 - val_loss: 0.0070 - val_accuracy: 0.5041
Epoch 164/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0015 - accuracy: 0.6421 - val_loss: 0.0069 - val_accuracy: 0.4939
Epoch 165/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0017 - accuracy: 0.6192 - val_loss: 0.0068 - val_accuracy: 0.5102
Epoch 166/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0016 - accuracy: 0.6304 - val_loss: 0.0072 - val_accuracy: 0.5183
Epoch 167/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0018 - accuracy: 0.6167 - val_loss: 0.0071 - val_accuracy: 0.5102
Epoch 168/200
62/62 [==============================] - 0s 3ms/step - loss: 0.0021 - accuracy: 0.6060 - val_loss: 0.0070 - val_accuracy: 0.5020
Epoch 169/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0021 - accuracy: 0.6080 - val_loss: 0.0069 - val_accuracy: 0.5061
Epoch 170/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0018 - accuracy: 0.6187 - val_loss: 0.0070 - val_accuracy: 0.4675
Epoch 171/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0016 - accuracy: 0.6167 - val_loss: 0.0068 - val_accuracy: 0.4939
Epoch 172/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0015 - accuracy: 0.6197 - val_loss: 0.0067 - val_accuracy: 0.5122
Epoch 173/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0015 - accuracy: 0.6258 - val_loss: 0.0068 - val_accuracy: 0.5203
Epoch 174/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0016 - accuracy: 0.6263 - val_loss: 0.0068 - val_accuracy: 0.5041
Epoch 175/200
62/62 [==============================] - 0s 3ms/step - loss: 0.0016 - accuracy: 0.6304 - val_loss: 0.0067 - val_accuracy: 0.4837
Epoch 176/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0016 - accuracy: 0.6202 - val_loss: 0.0065 - val_accuracy: 0.5142
Epoch 177/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0015 - accuracy: 0.6304 - val_loss: 0.0067 - val_accuracy: 0.5020
Epoch 178/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0016 - accuracy: 0.6355 - val_loss: 0.0064 - val_accuracy: 0.5183
Epoch 179/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0016 - accuracy: 0.6294 - val_loss: 0.0069 - val_accuracy: 0.5102
Epoch 180/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0015 - accuracy: 0.6289 - val_loss: 0.0066 - val_accuracy: 0.5000
Epoch 181/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0015 - accuracy: 0.6319 - val_loss: 0.0070 - val_accuracy: 0.5163
Epoch 182/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0015 - accuracy: 0.6406 - val_loss: 0.0067 - val_accuracy: 0.4919
Epoch 183/200
62/62 [==============================] - 0s 3ms/step - loss: 0.0016 - accuracy: 0.6238 - val_loss: 0.0071 - val_accuracy: 0.4980
Epoch 184/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0019 - accuracy: 0.6075 - val_loss: 0.0068 - val_accuracy: 0.4736
Epoch 185/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0019 - accuracy: 0.5948 - val_loss: 0.0069 - val_accuracy: 0.4573
Epoch 186/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0022 - accuracy: 0.6004 - val_loss: 0.0075 - val_accuracy: 0.4858
Epoch 187/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0021 - accuracy: 0.6009 - val_loss: 0.0071 - val_accuracy: 0.5041
Epoch 188/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0020 - accuracy: 0.6024 - val_loss: 0.0071 - val_accuracy: 0.4614
Epoch 189/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0019 - accuracy: 0.6192 - val_loss: 0.0076 - val_accuracy: 0.5081
Epoch 190/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0023 - accuracy: 0.6029 - val_loss: 0.0069 - val_accuracy: 0.4776
Epoch 191/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0023 - accuracy: 0.6004 - val_loss: 0.0079 - val_accuracy: 0.5203
Epoch 192/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0021 - accuracy: 0.6238 - val_loss: 0.0069 - val_accuracy: 0.4959
Epoch 193/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0018 - accuracy: 0.6157 - val_loss: 0.0068 - val_accuracy: 0.5142
Epoch 194/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0017 - accuracy: 0.6274 - val_loss: 0.0065 - val_accuracy: 0.5203
Epoch 195/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0016 - accuracy: 0.6197 - val_loss: 0.0068 - val_accuracy: 0.5224
Epoch 196/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0015 - accuracy: 0.6375 - val_loss: 0.0068 - val_accuracy: 0.5061
Epoch 197/200
62/62 [==============================] - 0s 3ms/step - loss: 0.0013 - accuracy: 0.6446 - val_loss: 0.0064 - val_accuracy: 0.5346
Epoch 198/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0013 - accuracy: 0.6299 - val_loss: 0.0065 - val_accuracy: 0.5203
Epoch 199/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0014 - accuracy: 0.6350 - val_loss: 0.0071 - val_accuracy: 0.5061
Epoch 200/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0017 - accuracy: 0.6192 - val_loss: 0.0067 - val_accuracy: 0.5183
In [ ]:
model.save('/content/gdrive/MyDrive/DLS/HW2/model_denoise.h5')

/usr/local/lib/python3.10/dist-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.
  saving_api.save_model(
In [ ]:
from keras.models import load_model
model = load_model('/content/gdrive/MyDrive/DLS/HW2/model_denoise.h5')
In [ ]:
#load noisy signal for validation
x_test,sr =librosa.load('data/test_x_01.wav' , sr = None)
X_test = librosa.stft(x_test, n_fft = 1024, hop_length = 512).T
X_test_mod = np.abs(X_test)
In [ ]:
X_test_mod.shape
Out[ ]:
(142, 513)
In [ ]:
S_test_mod = model.predict(X_test_mod)
S_complex = np.multiply(np.divide(X_test, X_test_mod), S_test_mod)
#time domain signal
#apply ifft
s_test = librosa.istft(S_complex.T , win_length = 1024, hop_length = 512)
#reconstructed wav
sf.write('test_s_01_recons.wav', s_test, sr)

5/5 [==============================] - 0s 2ms/step
In [ ]:
#snr:
#clean speech:
s , sr = librosa.load('data/test_s_01.wav')
#recovered speech:
shat, _ = librosa.load('test_s_01_recons.wav')

#truncate both to same length
min_length = min(len(s), len(shat))
s = s[:min_length]
shat = shat[:min_length]

#clean speech power
s_pow = np.sum(np.square(s))
#recovered speech power
noise_pow = np.sum(np.square(s-shat)) + 1e-20

#snr
snr_test1 = 10 * np.log10(s_pow / noise_pow)
snr_test1
Out[ ]:
9.716456314611452
In [ ]:
#embed the test 1 noisy audio file
from IPython.display import Audio
wn = Audio('data/test_x_01.wav', autoplay=True)
display(wn)
Your browser does not support the audio element.
In [ ]:
#embed the test 1 reconstructed audio file
from IPython.display import Audio
wn = Audio('test_s_01_recons.wav', autoplay=True)
display(wn)
Your browser does not support the audio element.
In [ ]:
#test on second signal
#load noisy signal for validation
x_test2,sr =librosa.load('data/test_x_02.wav' , sr = None)
X_test2 = librosa.stft(x_test2, n_fft = 1024, hop_length = 512).T
X_test2_mod = np.abs(X_test2)

#predict clean magnitude spectra
S_test2_mod = model.predict(X_test2_mod)
S_complex2 = np.multiply(np.divide(X_test2, X_test2_mod), S_test2_mod)

#time domain signal
#apply ifft
s_test2 = librosa.istft(S_complex2.T , win_length = 1024, hop_length = 512)

#reconstructed wav
sf.write('test_s_02_recons.wav', s_test2, sr)

12/12 [==============================] - 0s 1ms/step
In [ ]:
#embed the test 2 audio file
from IPython.display import Audio
wn = Audio('data/test_x_02.wav', autoplay=True)
display(wn)
Your browser does not support the audio element.
In [ ]:
#embed the test 2 reconstructed audio file
from IPython.display import Audio
wn = Audio('test_s_02_recons.wav', autoplay=True)
display(wn)
Your browser does not support the audio element.

Q2.

In [ ]:
#1D CNN does speech denoising in the stft magnitude domain
#1D CNN does convolution on any one axis , here the frequency axis.
#only one channel with magnitude unlike images that have 3 channels.

#dimensionality of minibatch : BX1X1X513
#kernel : 1XD
#output feature map: B X K X 1 X (513 - D -1)
#output matrix B X 513
In [ ]:
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Conv1D, MaxPooling1D, Flatten, Dense, Dropout
from tensorflow.keras.optimizers import Adam

experiments:

  • 16,16 32,8, pool, strides 2, relu - all
  • batch size 32 snr: 4.5 lr 0.002 , loss 0.005
  • batch size 128 snr: 7.79 lr 0.0002 , loss : 0.004
  • removing dropout. size 128 snr:9.54 , loss : e-4 , second half is better
  • removing dropout and a dense,size 128, lr 0.002 snr :10.76 loss 0.0024 - still disturbance
  • removing dropout and a dense,size 32, lr 0.001 snr: 9 loss:
In [ ]:
model_1dcnn = Sequential()

#input (513 ,1)
model_1dcnn.add(Conv1D(filters = 16, kernel_size = 16, padding = "same", activation = "relu", input_shape = (513 , 1)))
#(513, 32)
model_1dcnn.add(MaxPooling1D(pool_size = 2 , strides = 2))
#(256, 32)
model_1dcnn.add(Conv1D(32, 8, padding = "same", strides =1 , activation = "relu"))
model_1dcnn.add(MaxPooling1D(pool_size = 2, strides = 2))
#(128, 64)
model_1dcnn.add(Flatten())
#model_1dcnn.add(Dense(1024, activation ="relu"))
#model_1dcnn.add(Dropout(0.3))
model_1dcnn.add(Dense(513, activation = "relu"))
In [ ]:
model_1dcnn.summary()

Model: "sequential_1"
_________________________________________________________________
 Layer (type)                Output Shape              Param #   
=================================================================
 conv1d (Conv1D)             (None, 513, 16)           272       
                                                                 
 max_pooling1d (MaxPooling1  (None, 256, 16)           0         
 D)                                                              
                                                                 
 conv1d_1 (Conv1D)           (None, 256, 32)           4128      
                                                                 
 max_pooling1d_1 (MaxPoolin  (None, 128, 32)           0         
 g1D)                                                            
                                                                 
 flatten (Flatten)           (None, 4096)              0         
                                                                 
 dense_3 (Dense)             (None, 513)               2101761   
                                                                 
=================================================================
Total params: 2106161 (8.03 MB)
Trainable params: 2106161 (8.03 MB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
In [ ]:
model_1dcnn.compile(optimizer = Adam(learning_rate = 0.001) , loss = "mse", metrics = ["accuracy"])
history_1dcnn = model_1dcnn.fit(X_mag, S_mag, epochs = 200, batch_size = 32, validation_split = 0.2)

Epoch 1/200
62/62 [==============================] - 7s 7ms/step - loss: 0.0595 - accuracy: 0.0941 - val_loss: 0.0372 - val_accuracy: 0.1911
Epoch 2/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0258 - accuracy: 0.2700 - val_loss: 0.0260 - val_accuracy: 0.2724
Epoch 3/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0182 - accuracy: 0.3269 - val_loss: 0.0196 - val_accuracy: 0.3191
Epoch 4/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0134 - accuracy: 0.3696 - val_loss: 0.0170 - val_accuracy: 0.3435
Epoch 5/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0112 - accuracy: 0.4174 - val_loss: 0.0159 - val_accuracy: 0.3577
Epoch 6/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0097 - accuracy: 0.4347 - val_loss: 0.0145 - val_accuracy: 0.3943
Epoch 7/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0089 - accuracy: 0.4479 - val_loss: 0.0138 - val_accuracy: 0.3943
Epoch 8/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0081 - accuracy: 0.4616 - val_loss: 0.0132 - val_accuracy: 0.3943
Epoch 9/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0078 - accuracy: 0.4616 - val_loss: 0.0130 - val_accuracy: 0.3923
Epoch 10/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0073 - accuracy: 0.4779 - val_loss: 0.0127 - val_accuracy: 0.4126
Epoch 11/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0069 - accuracy: 0.4860 - val_loss: 0.0123 - val_accuracy: 0.4126
Epoch 12/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0066 - accuracy: 0.4962 - val_loss: 0.0120 - val_accuracy: 0.4289
Epoch 13/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0064 - accuracy: 0.4967 - val_loss: 0.0121 - val_accuracy: 0.4187
Epoch 14/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0063 - accuracy: 0.5058 - val_loss: 0.0119 - val_accuracy: 0.4167
Epoch 15/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0062 - accuracy: 0.5119 - val_loss: 0.0117 - val_accuracy: 0.4309
Epoch 16/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0060 - accuracy: 0.5175 - val_loss: 0.0120 - val_accuracy: 0.4248
Epoch 17/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0059 - accuracy: 0.5211 - val_loss: 0.0115 - val_accuracy: 0.4329
Epoch 18/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0057 - accuracy: 0.5247 - val_loss: 0.0115 - val_accuracy: 0.4431
Epoch 19/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0055 - accuracy: 0.5262 - val_loss: 0.0115 - val_accuracy: 0.4431
Epoch 20/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0055 - accuracy: 0.5384 - val_loss: 0.0111 - val_accuracy: 0.4411
Epoch 21/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0057 - accuracy: 0.5267 - val_loss: 0.0113 - val_accuracy: 0.4512
Epoch 22/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0054 - accuracy: 0.5353 - val_loss: 0.0108 - val_accuracy: 0.4390
Epoch 23/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0052 - accuracy: 0.5308 - val_loss: 0.0110 - val_accuracy: 0.4390
Epoch 24/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0050 - accuracy: 0.5440 - val_loss: 0.0109 - val_accuracy: 0.4472
Epoch 25/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0048 - accuracy: 0.5470 - val_loss: 0.0107 - val_accuracy: 0.4451
Epoch 26/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0048 - accuracy: 0.5531 - val_loss: 0.0106 - val_accuracy: 0.4533
Epoch 27/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0047 - accuracy: 0.5516 - val_loss: 0.0108 - val_accuracy: 0.4431
Epoch 28/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0046 - accuracy: 0.5587 - val_loss: 0.0106 - val_accuracy: 0.4553
Epoch 29/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0047 - accuracy: 0.5638 - val_loss: 0.0105 - val_accuracy: 0.4492
Epoch 30/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0045 - accuracy: 0.5648 - val_loss: 0.0107 - val_accuracy: 0.4553
Epoch 31/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0046 - accuracy: 0.5684 - val_loss: 0.0105 - val_accuracy: 0.4390
Epoch 32/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0044 - accuracy: 0.5663 - val_loss: 0.0107 - val_accuracy: 0.4614
Epoch 33/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0045 - accuracy: 0.5597 - val_loss: 0.0104 - val_accuracy: 0.4634
Epoch 34/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0043 - accuracy: 0.5755 - val_loss: 0.0103 - val_accuracy: 0.4492
Epoch 35/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0043 - accuracy: 0.5694 - val_loss: 0.0102 - val_accuracy: 0.4675
Epoch 36/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0044 - accuracy: 0.5735 - val_loss: 0.0104 - val_accuracy: 0.4451
Epoch 37/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0043 - accuracy: 0.5735 - val_loss: 0.0105 - val_accuracy: 0.4472
Epoch 38/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0042 - accuracy: 0.5760 - val_loss: 0.0103 - val_accuracy: 0.4553
Epoch 39/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0042 - accuracy: 0.5785 - val_loss: 0.0106 - val_accuracy: 0.4492
Epoch 40/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0041 - accuracy: 0.5750 - val_loss: 0.0101 - val_accuracy: 0.4593
Epoch 41/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0040 - accuracy: 0.5785 - val_loss: 0.0103 - val_accuracy: 0.4492
Epoch 42/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0040 - accuracy: 0.5796 - val_loss: 0.0101 - val_accuracy: 0.4512
Epoch 43/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0041 - accuracy: 0.5826 - val_loss: 0.0099 - val_accuracy: 0.4472
Epoch 44/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0039 - accuracy: 0.5877 - val_loss: 0.0099 - val_accuracy: 0.4593
Epoch 45/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0038 - accuracy: 0.5872 - val_loss: 0.0099 - val_accuracy: 0.4715
Epoch 46/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0037 - accuracy: 0.5907 - val_loss: 0.0099 - val_accuracy: 0.4614
Epoch 47/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0037 - accuracy: 0.5882 - val_loss: 0.0100 - val_accuracy: 0.4675
Epoch 48/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0038 - accuracy: 0.5867 - val_loss: 0.0100 - val_accuracy: 0.4675
Epoch 49/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0037 - accuracy: 0.5887 - val_loss: 0.0100 - val_accuracy: 0.4512
Epoch 50/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0037 - accuracy: 0.5933 - val_loss: 0.0100 - val_accuracy: 0.4512
Epoch 51/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0037 - accuracy: 0.5867 - val_loss: 0.0099 - val_accuracy: 0.4736
Epoch 52/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0037 - accuracy: 0.5907 - val_loss: 0.0100 - val_accuracy: 0.4553
Epoch 53/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0036 - accuracy: 0.6009 - val_loss: 0.0098 - val_accuracy: 0.4512
Epoch 54/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0036 - accuracy: 0.5913 - val_loss: 0.0098 - val_accuracy: 0.4634
Epoch 55/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0036 - accuracy: 0.6014 - val_loss: 0.0097 - val_accuracy: 0.4654
Epoch 56/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0036 - accuracy: 0.5989 - val_loss: 0.0098 - val_accuracy: 0.4634
Epoch 57/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0038 - accuracy: 0.5918 - val_loss: 0.0098 - val_accuracy: 0.4553
Epoch 58/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0036 - accuracy: 0.5979 - val_loss: 0.0105 - val_accuracy: 0.4614
Epoch 59/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0041 - accuracy: 0.5923 - val_loss: 0.0100 - val_accuracy: 0.4634
Epoch 60/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0039 - accuracy: 0.5846 - val_loss: 0.0097 - val_accuracy: 0.4593
Epoch 61/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0037 - accuracy: 0.6019 - val_loss: 0.0097 - val_accuracy: 0.4776
Epoch 62/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0035 - accuracy: 0.5974 - val_loss: 0.0097 - val_accuracy: 0.4533
Epoch 63/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0037 - accuracy: 0.5913 - val_loss: 0.0096 - val_accuracy: 0.4512
Epoch 64/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0034 - accuracy: 0.6126 - val_loss: 0.0096 - val_accuracy: 0.4390
Epoch 65/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0033 - accuracy: 0.6045 - val_loss: 0.0095 - val_accuracy: 0.4553
Epoch 66/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0032 - accuracy: 0.6131 - val_loss: 0.0096 - val_accuracy: 0.4492
Epoch 67/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0033 - accuracy: 0.6151 - val_loss: 0.0094 - val_accuracy: 0.4654
Epoch 68/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0033 - accuracy: 0.6101 - val_loss: 0.0098 - val_accuracy: 0.4654
Epoch 69/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0034 - accuracy: 0.6167 - val_loss: 0.0095 - val_accuracy: 0.4695
Epoch 70/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0033 - accuracy: 0.6080 - val_loss: 0.0094 - val_accuracy: 0.4695
Epoch 71/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0033 - accuracy: 0.6131 - val_loss: 0.0094 - val_accuracy: 0.4614
Epoch 72/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0034 - accuracy: 0.6065 - val_loss: 0.0098 - val_accuracy: 0.4512
Epoch 73/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0033 - accuracy: 0.6090 - val_loss: 0.0094 - val_accuracy: 0.4533
Epoch 74/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0031 - accuracy: 0.6101 - val_loss: 0.0094 - val_accuracy: 0.4573
Epoch 75/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0031 - accuracy: 0.6136 - val_loss: 0.0094 - val_accuracy: 0.4492
Epoch 76/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0031 - accuracy: 0.6126 - val_loss: 0.0095 - val_accuracy: 0.4614
Epoch 77/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0031 - accuracy: 0.6218 - val_loss: 0.0094 - val_accuracy: 0.4593
Epoch 78/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0033 - accuracy: 0.6146 - val_loss: 0.0095 - val_accuracy: 0.4756
Epoch 79/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0033 - accuracy: 0.6085 - val_loss: 0.0094 - val_accuracy: 0.4451
Epoch 80/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0032 - accuracy: 0.6080 - val_loss: 0.0095 - val_accuracy: 0.4573
Epoch 81/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0033 - accuracy: 0.6162 - val_loss: 0.0096 - val_accuracy: 0.4553
Epoch 82/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0033 - accuracy: 0.6075 - val_loss: 0.0092 - val_accuracy: 0.4675
Epoch 83/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0031 - accuracy: 0.6121 - val_loss: 0.0092 - val_accuracy: 0.4634
Epoch 84/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0031 - accuracy: 0.6202 - val_loss: 0.0093 - val_accuracy: 0.4634
Epoch 85/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0031 - accuracy: 0.6126 - val_loss: 0.0092 - val_accuracy: 0.4695
Epoch 86/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0030 - accuracy: 0.6314 - val_loss: 0.0092 - val_accuracy: 0.4675
Epoch 87/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0033 - accuracy: 0.6197 - val_loss: 0.0097 - val_accuracy: 0.4553
Epoch 88/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0037 - accuracy: 0.6136 - val_loss: 0.0098 - val_accuracy: 0.4573
Epoch 89/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0033 - accuracy: 0.6080 - val_loss: 0.0090 - val_accuracy: 0.4715
Epoch 90/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0030 - accuracy: 0.6187 - val_loss: 0.0090 - val_accuracy: 0.4634
Epoch 91/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0029 - accuracy: 0.6284 - val_loss: 0.0089 - val_accuracy: 0.4573
Epoch 92/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0028 - accuracy: 0.6263 - val_loss: 0.0090 - val_accuracy: 0.4634
Epoch 93/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0028 - accuracy: 0.6329 - val_loss: 0.0089 - val_accuracy: 0.4715
Epoch 94/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0028 - accuracy: 0.6355 - val_loss: 0.0090 - val_accuracy: 0.4614
Epoch 95/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0028 - accuracy: 0.6329 - val_loss: 0.0092 - val_accuracy: 0.4736
Epoch 96/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0028 - accuracy: 0.6441 - val_loss: 0.0090 - val_accuracy: 0.4593
Epoch 97/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0028 - accuracy: 0.6263 - val_loss: 0.0091 - val_accuracy: 0.4553
Epoch 98/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0029 - accuracy: 0.6324 - val_loss: 0.0091 - val_accuracy: 0.4512
Epoch 99/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0028 - accuracy: 0.6335 - val_loss: 0.0090 - val_accuracy: 0.4797
Epoch 100/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0030 - accuracy: 0.6335 - val_loss: 0.0091 - val_accuracy: 0.4654
Epoch 101/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0029 - accuracy: 0.6345 - val_loss: 0.0090 - val_accuracy: 0.4675
Epoch 102/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0027 - accuracy: 0.6319 - val_loss: 0.0091 - val_accuracy: 0.4675
Epoch 103/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0027 - accuracy: 0.6350 - val_loss: 0.0089 - val_accuracy: 0.4675
Epoch 104/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0028 - accuracy: 0.6355 - val_loss: 0.0091 - val_accuracy: 0.4533
Epoch 105/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0028 - accuracy: 0.6340 - val_loss: 0.0089 - val_accuracy: 0.4634
Epoch 106/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0027 - accuracy: 0.6426 - val_loss: 0.0091 - val_accuracy: 0.4512
Epoch 107/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0027 - accuracy: 0.6329 - val_loss: 0.0089 - val_accuracy: 0.4654
Epoch 108/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0026 - accuracy: 0.6396 - val_loss: 0.0089 - val_accuracy: 0.4634
Epoch 109/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0027 - accuracy: 0.6421 - val_loss: 0.0088 - val_accuracy: 0.4634
Epoch 110/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0026 - accuracy: 0.6482 - val_loss: 0.0089 - val_accuracy: 0.4573
Epoch 111/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0027 - accuracy: 0.6472 - val_loss: 0.0089 - val_accuracy: 0.4512
Epoch 112/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0028 - accuracy: 0.6380 - val_loss: 0.0093 - val_accuracy: 0.4350
Epoch 113/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0028 - accuracy: 0.6375 - val_loss: 0.0091 - val_accuracy: 0.4736
Epoch 114/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0029 - accuracy: 0.6385 - val_loss: 0.0090 - val_accuracy: 0.4451
Epoch 115/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0028 - accuracy: 0.6335 - val_loss: 0.0091 - val_accuracy: 0.4533
Epoch 116/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0027 - accuracy: 0.6421 - val_loss: 0.0088 - val_accuracy: 0.4573
Epoch 117/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0027 - accuracy: 0.6426 - val_loss: 0.0087 - val_accuracy: 0.4553
Epoch 118/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0026 - accuracy: 0.6467 - val_loss: 0.0088 - val_accuracy: 0.4472
Epoch 119/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0026 - accuracy: 0.6431 - val_loss: 0.0087 - val_accuracy: 0.4695
Epoch 120/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0026 - accuracy: 0.6538 - val_loss: 0.0088 - val_accuracy: 0.4512
Epoch 121/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0025 - accuracy: 0.6492 - val_loss: 0.0088 - val_accuracy: 0.4593
Epoch 122/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0025 - accuracy: 0.6543 - val_loss: 0.0088 - val_accuracy: 0.4533
Epoch 123/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0025 - accuracy: 0.6507 - val_loss: 0.0087 - val_accuracy: 0.4553
Epoch 124/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0025 - accuracy: 0.6558 - val_loss: 0.0086 - val_accuracy: 0.4370
Epoch 125/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0025 - accuracy: 0.6507 - val_loss: 0.0087 - val_accuracy: 0.4512
Epoch 126/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0025 - accuracy: 0.6553 - val_loss: 0.0088 - val_accuracy: 0.4512
Epoch 127/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0025 - accuracy: 0.6579 - val_loss: 0.0089 - val_accuracy: 0.4695
Epoch 128/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0029 - accuracy: 0.6451 - val_loss: 0.0090 - val_accuracy: 0.4451
Epoch 129/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0028 - accuracy: 0.6436 - val_loss: 0.0089 - val_accuracy: 0.4431
Epoch 130/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0031 - accuracy: 0.6340 - val_loss: 0.0090 - val_accuracy: 0.4390
Epoch 131/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0031 - accuracy: 0.6314 - val_loss: 0.0097 - val_accuracy: 0.4533
Epoch 132/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0030 - accuracy: 0.6299 - val_loss: 0.0088 - val_accuracy: 0.4289
Epoch 133/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0026 - accuracy: 0.6390 - val_loss: 0.0087 - val_accuracy: 0.4370
Epoch 134/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0024 - accuracy: 0.6467 - val_loss: 0.0086 - val_accuracy: 0.4370
Epoch 135/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0024 - accuracy: 0.6512 - val_loss: 0.0086 - val_accuracy: 0.4411
Epoch 136/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0023 - accuracy: 0.6579 - val_loss: 0.0085 - val_accuracy: 0.4472
Epoch 137/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0023 - accuracy: 0.6660 - val_loss: 0.0085 - val_accuracy: 0.4431
Epoch 138/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0023 - accuracy: 0.6619 - val_loss: 0.0086 - val_accuracy: 0.4472
Epoch 139/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0023 - accuracy: 0.6624 - val_loss: 0.0085 - val_accuracy: 0.4492
Epoch 140/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0023 - accuracy: 0.6614 - val_loss: 0.0085 - val_accuracy: 0.4390
Epoch 141/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0023 - accuracy: 0.6655 - val_loss: 0.0085 - val_accuracy: 0.4472
Epoch 142/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0023 - accuracy: 0.6767 - val_loss: 0.0086 - val_accuracy: 0.4411
Epoch 143/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0023 - accuracy: 0.6589 - val_loss: 0.0085 - val_accuracy: 0.4533
Epoch 144/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0023 - accuracy: 0.6584 - val_loss: 0.0085 - val_accuracy: 0.4512
Epoch 145/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0023 - accuracy: 0.6614 - val_loss: 0.0085 - val_accuracy: 0.4472
Epoch 146/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0023 - accuracy: 0.6634 - val_loss: 0.0085 - val_accuracy: 0.4451
Epoch 147/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0022 - accuracy: 0.6741 - val_loss: 0.0085 - val_accuracy: 0.4451
Epoch 148/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0022 - accuracy: 0.6685 - val_loss: 0.0085 - val_accuracy: 0.4390
Epoch 149/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0024 - accuracy: 0.6553 - val_loss: 0.0086 - val_accuracy: 0.4492
Epoch 150/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0024 - accuracy: 0.6675 - val_loss: 0.0088 - val_accuracy: 0.4573
Epoch 151/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0024 - accuracy: 0.6533 - val_loss: 0.0087 - val_accuracy: 0.4573
Epoch 152/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0024 - accuracy: 0.6477 - val_loss: 0.0086 - val_accuracy: 0.4593
Epoch 153/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0023 - accuracy: 0.6584 - val_loss: 0.0087 - val_accuracy: 0.4431
Epoch 154/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0025 - accuracy: 0.6518 - val_loss: 0.0086 - val_accuracy: 0.4715
Epoch 155/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0025 - accuracy: 0.6528 - val_loss: 0.0084 - val_accuracy: 0.4492
Epoch 156/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0025 - accuracy: 0.6492 - val_loss: 0.0085 - val_accuracy: 0.4431
Epoch 157/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0024 - accuracy: 0.6594 - val_loss: 0.0085 - val_accuracy: 0.4390
Epoch 158/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0023 - accuracy: 0.6599 - val_loss: 0.0085 - val_accuracy: 0.4512
Epoch 159/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0024 - accuracy: 0.6629 - val_loss: 0.0085 - val_accuracy: 0.4492
Epoch 160/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0024 - accuracy: 0.6538 - val_loss: 0.0085 - val_accuracy: 0.4512
Epoch 161/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0022 - accuracy: 0.6665 - val_loss: 0.0085 - val_accuracy: 0.4614
Epoch 162/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0022 - accuracy: 0.6690 - val_loss: 0.0084 - val_accuracy: 0.4512
Epoch 163/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0022 - accuracy: 0.6670 - val_loss: 0.0085 - val_accuracy: 0.4390
Epoch 164/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0022 - accuracy: 0.6726 - val_loss: 0.0084 - val_accuracy: 0.4411
Epoch 165/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0022 - accuracy: 0.6746 - val_loss: 0.0085 - val_accuracy: 0.4451
Epoch 166/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0021 - accuracy: 0.6680 - val_loss: 0.0085 - val_accuracy: 0.4533
Epoch 167/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0023 - accuracy: 0.6629 - val_loss: 0.0084 - val_accuracy: 0.4654
Epoch 168/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0023 - accuracy: 0.6680 - val_loss: 0.0085 - val_accuracy: 0.4675
Epoch 169/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0022 - accuracy: 0.6756 - val_loss: 0.0084 - val_accuracy: 0.4634
Epoch 170/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0022 - accuracy: 0.6762 - val_loss: 0.0085 - val_accuracy: 0.4411
Epoch 171/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0021 - accuracy: 0.6695 - val_loss: 0.0084 - val_accuracy: 0.4512
Epoch 172/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0021 - accuracy: 0.6772 - val_loss: 0.0084 - val_accuracy: 0.4492
Epoch 173/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0021 - accuracy: 0.6802 - val_loss: 0.0084 - val_accuracy: 0.4472
Epoch 174/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0022 - accuracy: 0.6756 - val_loss: 0.0086 - val_accuracy: 0.4289
Epoch 175/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0025 - accuracy: 0.6584 - val_loss: 0.0085 - val_accuracy: 0.4309
Epoch 176/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0034 - accuracy: 0.6263 - val_loss: 0.0086 - val_accuracy: 0.4593
Epoch 177/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0029 - accuracy: 0.6477 - val_loss: 0.0085 - val_accuracy: 0.4492
Epoch 178/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0025 - accuracy: 0.6548 - val_loss: 0.0084 - val_accuracy: 0.4614
Epoch 179/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0022 - accuracy: 0.6619 - val_loss: 0.0083 - val_accuracy: 0.4553
Epoch 180/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0021 - accuracy: 0.6777 - val_loss: 0.0083 - val_accuracy: 0.4512
Epoch 181/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0020 - accuracy: 0.6751 - val_loss: 0.0084 - val_accuracy: 0.4593
Epoch 182/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0020 - accuracy: 0.6807 - val_loss: 0.0082 - val_accuracy: 0.4573
Epoch 183/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0020 - accuracy: 0.6889 - val_loss: 0.0083 - val_accuracy: 0.4492
Epoch 184/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0019 - accuracy: 0.6889 - val_loss: 0.0082 - val_accuracy: 0.4411
Epoch 185/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0019 - accuracy: 0.6843 - val_loss: 0.0083 - val_accuracy: 0.4492
Epoch 186/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0019 - accuracy: 0.6919 - val_loss: 0.0082 - val_accuracy: 0.4512
Epoch 187/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0019 - accuracy: 0.6929 - val_loss: 0.0083 - val_accuracy: 0.4573
Epoch 188/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0019 - accuracy: 0.6960 - val_loss: 0.0083 - val_accuracy: 0.4492
Epoch 189/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0019 - accuracy: 0.6929 - val_loss: 0.0083 - val_accuracy: 0.4512
Epoch 190/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0019 - accuracy: 0.6873 - val_loss: 0.0083 - val_accuracy: 0.4593
Epoch 191/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0019 - accuracy: 0.6960 - val_loss: 0.0083 - val_accuracy: 0.4533
Epoch 192/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0019 - accuracy: 0.6914 - val_loss: 0.0083 - val_accuracy: 0.4512
Epoch 193/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0020 - accuracy: 0.6909 - val_loss: 0.0083 - val_accuracy: 0.4492
Epoch 194/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0020 - accuracy: 0.6812 - val_loss: 0.0083 - val_accuracy: 0.4512
Epoch 195/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0021 - accuracy: 0.6863 - val_loss: 0.0082 - val_accuracy: 0.4431
Epoch 196/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0022 - accuracy: 0.6685 - val_loss: 0.0085 - val_accuracy: 0.4451
Epoch 197/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0024 - accuracy: 0.6507 - val_loss: 0.0085 - val_accuracy: 0.4634
Epoch 198/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0025 - accuracy: 0.6609 - val_loss: 0.0086 - val_accuracy: 0.4451
Epoch 199/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0023 - accuracy: 0.6650 - val_loss: 0.0090 - val_accuracy: 0.4512
Epoch 200/200
62/62 [==============================] - 0s 4ms/step - loss: 0.0024 - accuracy: 0.6756 - val_loss: 0.0084 - val_accuracy: 0.4614
In [ ]:
model_1dcnn.save('/content/gdrive/MyDrive/DLS/HW2/model1dcnn.h5')

/usr/local/lib/python3.10/dist-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.
  saving_api.save_model(
In [ ]:
#load noisy signal for validation
x_test,sr = librosa.load('data/test_x_01.wav' , sr = None)
X_test = librosa.stft(x_test, n_fft = 1024, hop_length = 512).T
X_test_mod = np.abs(X_test)
In [ ]:
from keras.models import load_model

model_1dcnn = load_model('model1dcnn.h5')

S_test_mod = model_1dcnn.predict(X_test_mod)
S_complex = np.multiply(np.divide(X_test, X_test_mod), S_test_mod)
#time domain signal
#apply ifft
s_test = librosa.istft(S_complex.T , win_length = 1024, hop_length = 512)
#reconstructed wav
sf.write('test_s_01_recons_1dcnn.wav', s_test, sr)

#snr:
#clean speech:
s , sr = librosa.load('data/test_s_01.wav')
#recovered speech:
shat, _ = librosa.load('test_s_01_recons_1dcnn.wav')

#truncate both to same length
min_length = min(len(s), len(shat))
s = s[:min_length]
shat = shat[:min_length]

#clean speech power
s_pow = np.sum(np.square(s))
#recovered speech power
noise_pow = np.sum(np.square(s-shat)) + 1e-20

#snr
snr_test1 = 10 * np.log10(s_pow / noise_pow)
snr_test1

5/5 [==============================] - 0s 6ms/step
Out[ ]:
8.886485974168945
In [ ]:
#test on second signal
#load noisy signal for validation
x_test2,sr =librosa.load('data/test_x_02.wav' , sr = None)
X_test2 = librosa.stft(x_test2, n_fft = 1024, hop_length = 512).T
X_test2_mod = np.abs(X_test2)

#predict clean magnitude spectra
S_test2_mod = model_1dcnn.predict(X_test2_mod)
S_complex2 = np.multiply(np.divide(X_test2, X_test2_mod), S_test2_mod)

#time domain signal
#apply ifft
s_test2 = librosa.istft(S_complex2.T , win_length = 1024, hop_length = 512)

#reconstructed wav
sf.write('test_s_02_recons_1dcnn.wav', s_test2, sr)

12/12 [==============================] - 0s 3ms/step
In [ ]:
#embed the test 2 audio file
from IPython.display import Audio
wn = Audio('data/test_x_02.wav', autoplay=True)
display(wn)
Your browser does not support the audio element.
In [ ]:
#embed the test 2 audio file
from IPython.display import Audio
wn = Audio('test_s_02_recons_1dcnn.wav', autoplay=True)
display(wn)
Your browser does not support the audio element.

Q3. (was done on kaggle)

a. Baseline

In [ ]:
from keras.datasets import cifar10
import keras
import tensorflow as tf
import numpy as np
from tensorflow.keras.layers import Conv2D, MaxPooling2D, Dense, Flatten, Dropout
from tensorflow.keras.models import Sequential
In [ ]:
(x_train, y_train), (x_test, y_test) = cifar10.load_data()

Downloading data from https://www.cs.toronto.edu/~kriz/cifar-10-python.tar.gz
170498071/170498071 [==============================] - 6s 0us/step
In [ ]:
#set aside 5000 examples for validation
x_val = x_train[-5000:]
y_val = y_train[-5000:]
x_train = x_train[:-5000]
y_train = y_train[:-5000]
In [ ]:
#reshape to 32x32x3
x_train = x_train.reshape(x_train.shape[0] , 32, 32, 3)
x_test = x_test.reshape(x_test.shape[0], 32, 32, 3)
x_val = x_val.reshape(x_val.shape[0], 32, 32, 3)
In [ ]:
x_train = x_train.astype('float32')
x_test = y_test.astype('float32')
x_val = x_val.astype('float32')
In [ ]:
#normalize to -1 to 1
x_train = x_train/255.0
x_val = x_val/255.0

x_train = x_train * 2 - 1
x_val = x_val * 2 - 1
In [ ]:
#categorical classes
y_train = keras.utils.to_categorical(y_train, 10)
y_val = keras.utils.to_categorical(y_val, 10)
In [ ]:
#model
model = Sequential()
model.add(Conv2D(filters = 10, kernel_size = (5, 5) , strides = (1, 1), padding = "same",input_shape = (32,32,3),
                 activation = "relu", kernel_initializer = "he_normal"))
model.add(MaxPooling2D(pool_size = (2, 2), strides = (2, 2)))
model.add(Conv2D(filters = 10, kernel_size = (5, 5) , strides = (1, 1), padding = "same",
                 activation = "relu", kernel_initializer = "he_normal"))
model.add(MaxPooling2D(pool_size = (2, 2), strides = (2, 2)))
model.add(Flatten())
model.add(Dense(20, activation = "relu", kernel_initializer = "he_normal"))
model.add(Dense(10, activation = "softmax"))
In [ ]:
model.compile(optimizer = 'Adam', loss = "mse", metrics = ['accuracy'])
history_baseline = model.fit(x_train, y_train, epochs = 200 ,batch_size = 32, validation_data = (x_val, y_val))

Epoch 1/200
1407/1407 [==============================] - 10s 6ms/step - loss: 0.0710 - accuracy: 0.4163 - val_loss: 0.0655 - val_accuracy: 0.4938
Epoch 2/200
1407/1407 [==============================] - 6s 5ms/step - loss: 0.0589 - accuracy: 0.5456 - val_loss: 0.0551 - val_accuracy: 0.5816
Epoch 3/200
1407/1407 [==============================] - 5s 4ms/step - loss: 0.0544 - accuracy: 0.5865 - val_loss: 0.0529 - val_accuracy: 0.6028
Epoch 4/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0509 - accuracy: 0.6197 - val_loss: 0.0506 - val_accuracy: 0.6234
Epoch 5/200
1407/1407 [==============================] - 5s 4ms/step - loss: 0.0489 - accuracy: 0.6374 - val_loss: 0.0508 - val_accuracy: 0.6234
Epoch 6/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0471 - accuracy: 0.6527 - val_loss: 0.0486 - val_accuracy: 0.6418
Epoch 7/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0462 - accuracy: 0.6619 - val_loss: 0.0487 - val_accuracy: 0.6432
Epoch 8/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0450 - accuracy: 0.6723 - val_loss: 0.0472 - val_accuracy: 0.6520
Epoch 9/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0443 - accuracy: 0.6767 - val_loss: 0.0477 - val_accuracy: 0.6478
Epoch 10/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0435 - accuracy: 0.6847 - val_loss: 0.0466 - val_accuracy: 0.6552
Epoch 11/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0431 - accuracy: 0.6884 - val_loss: 0.0464 - val_accuracy: 0.6586
Epoch 12/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0425 - accuracy: 0.6944 - val_loss: 0.0464 - val_accuracy: 0.6662
Epoch 13/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0421 - accuracy: 0.6966 - val_loss: 0.0456 - val_accuracy: 0.6626
Epoch 14/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0416 - accuracy: 0.7005 - val_loss: 0.0472 - val_accuracy: 0.6540
Epoch 15/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0411 - accuracy: 0.7055 - val_loss: 0.0475 - val_accuracy: 0.6534
Epoch 16/200
1407/1407 [==============================] - 5s 4ms/step - loss: 0.0408 - accuracy: 0.7081 - val_loss: 0.0464 - val_accuracy: 0.6654
Epoch 17/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0403 - accuracy: 0.7130 - val_loss: 0.0477 - val_accuracy: 0.6518
Epoch 18/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0400 - accuracy: 0.7142 - val_loss: 0.0466 - val_accuracy: 0.6610
Epoch 19/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0397 - accuracy: 0.7172 - val_loss: 0.0462 - val_accuracy: 0.6642
Epoch 20/200
1407/1407 [==============================] - 5s 4ms/step - loss: 0.0395 - accuracy: 0.7185 - val_loss: 0.0464 - val_accuracy: 0.6638
Epoch 21/200
1407/1407 [==============================] - 5s 4ms/step - loss: 0.0394 - accuracy: 0.7193 - val_loss: 0.0467 - val_accuracy: 0.6608
Epoch 22/200
1407/1407 [==============================] - 5s 4ms/step - loss: 0.0391 - accuracy: 0.7233 - val_loss: 0.0460 - val_accuracy: 0.6682
Epoch 23/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0387 - accuracy: 0.7252 - val_loss: 0.0467 - val_accuracy: 0.6574
Epoch 24/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0386 - accuracy: 0.7275 - val_loss: 0.0469 - val_accuracy: 0.6644
Epoch 25/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0384 - accuracy: 0.7292 - val_loss: 0.0468 - val_accuracy: 0.6616
Epoch 26/200
1407/1407 [==============================] - 5s 4ms/step - loss: 0.0381 - accuracy: 0.7307 - val_loss: 0.0482 - val_accuracy: 0.6510
Epoch 27/200
1407/1407 [==============================] - 5s 4ms/step - loss: 0.0381 - accuracy: 0.7308 - val_loss: 0.0469 - val_accuracy: 0.6622
Epoch 28/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0379 - accuracy: 0.7345 - val_loss: 0.0492 - val_accuracy: 0.6452
Epoch 29/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0377 - accuracy: 0.7345 - val_loss: 0.0470 - val_accuracy: 0.6646
Epoch 30/200
1407/1407 [==============================] - 5s 4ms/step - loss: 0.0374 - accuracy: 0.7376 - val_loss: 0.0481 - val_accuracy: 0.6588
Epoch 31/200
1407/1407 [==============================] - 5s 4ms/step - loss: 0.0374 - accuracy: 0.7381 - val_loss: 0.0481 - val_accuracy: 0.6514
Epoch 32/200
1407/1407 [==============================] - 5s 4ms/step - loss: 0.0372 - accuracy: 0.7400 - val_loss: 0.0505 - val_accuracy: 0.6332
Epoch 33/200
1407/1407 [==============================] - 5s 4ms/step - loss: 0.0372 - accuracy: 0.7402 - val_loss: 0.0485 - val_accuracy: 0.6506
Epoch 34/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0370 - accuracy: 0.7412 - val_loss: 0.0484 - val_accuracy: 0.6570
Epoch 35/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0369 - accuracy: 0.7430 - val_loss: 0.0474 - val_accuracy: 0.6566
Epoch 36/200
1407/1407 [==============================] - 5s 4ms/step - loss: 0.0367 - accuracy: 0.7438 - val_loss: 0.0486 - val_accuracy: 0.6480
Epoch 37/200
1407/1407 [==============================] - 5s 4ms/step - loss: 0.0368 - accuracy: 0.7452 - val_loss: 0.0499 - val_accuracy: 0.6444
Epoch 38/200
1407/1407 [==============================] - 5s 4ms/step - loss: 0.0365 - accuracy: 0.7466 - val_loss: 0.0490 - val_accuracy: 0.6534
Epoch 39/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0364 - accuracy: 0.7471 - val_loss: 0.0495 - val_accuracy: 0.6448
Epoch 40/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0362 - accuracy: 0.7500 - val_loss: 0.0495 - val_accuracy: 0.6526
Epoch 41/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0362 - accuracy: 0.7488 - val_loss: 0.0506 - val_accuracy: 0.6400
Epoch 42/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0361 - accuracy: 0.7500 - val_loss: 0.0485 - val_accuracy: 0.6550
Epoch 43/200
1407/1407 [==============================] - 5s 4ms/step - loss: 0.0359 - accuracy: 0.7514 - val_loss: 0.0486 - val_accuracy: 0.6572
Epoch 44/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0356 - accuracy: 0.7537 - val_loss: 0.0491 - val_accuracy: 0.6570
Epoch 45/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0357 - accuracy: 0.7532 - val_loss: 0.0494 - val_accuracy: 0.6522
Epoch 46/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0357 - accuracy: 0.7532 - val_loss: 0.0496 - val_accuracy: 0.6520
Epoch 47/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0356 - accuracy: 0.7540 - val_loss: 0.0492 - val_accuracy: 0.6548
Epoch 48/200
1407/1407 [==============================] - 5s 4ms/step - loss: 0.0356 - accuracy: 0.7549 - val_loss: 0.0502 - val_accuracy: 0.6462
Epoch 49/200
1407/1407 [==============================] - 5s 4ms/step - loss: 0.0352 - accuracy: 0.7582 - val_loss: 0.0500 - val_accuracy: 0.6506
Epoch 50/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0353 - accuracy: 0.7580 - val_loss: 0.0503 - val_accuracy: 0.6452
Epoch 51/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0353 - accuracy: 0.7569 - val_loss: 0.0494 - val_accuracy: 0.6480
Epoch 52/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0349 - accuracy: 0.7619 - val_loss: 0.0510 - val_accuracy: 0.6514
Epoch 53/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0350 - accuracy: 0.7608 - val_loss: 0.0526 - val_accuracy: 0.6350
Epoch 54/200
1407/1407 [==============================] - 5s 4ms/step - loss: 0.0349 - accuracy: 0.7596 - val_loss: 0.0488 - val_accuracy: 0.6600
Epoch 55/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0349 - accuracy: 0.7620 - val_loss: 0.0494 - val_accuracy: 0.6526
Epoch 56/200
1407/1407 [==============================] - 5s 4ms/step - loss: 0.0346 - accuracy: 0.7633 - val_loss: 0.0490 - val_accuracy: 0.6534
Epoch 57/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0348 - accuracy: 0.7617 - val_loss: 0.0506 - val_accuracy: 0.6468
Epoch 58/200
1407/1407 [==============================] - 5s 4ms/step - loss: 0.0348 - accuracy: 0.7621 - val_loss: 0.0503 - val_accuracy: 0.6472
Epoch 59/200
1407/1407 [==============================] - 5s 4ms/step - loss: 0.0345 - accuracy: 0.7649 - val_loss: 0.0495 - val_accuracy: 0.6524
Epoch 60/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0345 - accuracy: 0.7643 - val_loss: 0.0501 - val_accuracy: 0.6438
Epoch 61/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0344 - accuracy: 0.7658 - val_loss: 0.0505 - val_accuracy: 0.6474
Epoch 62/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0342 - accuracy: 0.7681 - val_loss: 0.0513 - val_accuracy: 0.6426
Epoch 63/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0345 - accuracy: 0.7645 - val_loss: 0.0510 - val_accuracy: 0.6478
Epoch 64/200
1407/1407 [==============================] - 5s 4ms/step - loss: 0.0342 - accuracy: 0.7672 - val_loss: 0.0515 - val_accuracy: 0.6406
Epoch 65/200
1407/1407 [==============================] - 5s 4ms/step - loss: 0.0344 - accuracy: 0.7650 - val_loss: 0.0512 - val_accuracy: 0.6448
Epoch 66/200
1407/1407 [==============================] - 5s 4ms/step - loss: 0.0340 - accuracy: 0.7693 - val_loss: 0.0537 - val_accuracy: 0.6302
Epoch 67/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0340 - accuracy: 0.7696 - val_loss: 0.0512 - val_accuracy: 0.6424
Epoch 68/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0340 - accuracy: 0.7696 - val_loss: 0.0498 - val_accuracy: 0.6592
Epoch 69/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0339 - accuracy: 0.7696 - val_loss: 0.0507 - val_accuracy: 0.6512
Epoch 70/200
1407/1407 [==============================] - 5s 4ms/step - loss: 0.0339 - accuracy: 0.7706 - val_loss: 0.0522 - val_accuracy: 0.6414
Epoch 71/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0337 - accuracy: 0.7715 - val_loss: 0.0501 - val_accuracy: 0.6492
Epoch 72/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0337 - accuracy: 0.7717 - val_loss: 0.0517 - val_accuracy: 0.6456
Epoch 73/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0336 - accuracy: 0.7735 - val_loss: 0.0530 - val_accuracy: 0.6352
Epoch 74/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0338 - accuracy: 0.7713 - val_loss: 0.0514 - val_accuracy: 0.6446
Epoch 75/200
1407/1407 [==============================] - 5s 4ms/step - loss: 0.0336 - accuracy: 0.7729 - val_loss: 0.0523 - val_accuracy: 0.6370
Epoch 76/200
1407/1407 [==============================] - 5s 4ms/step - loss: 0.0336 - accuracy: 0.7729 - val_loss: 0.0531 - val_accuracy: 0.6324
Epoch 77/200
1407/1407 [==============================] - 5s 4ms/step - loss: 0.0334 - accuracy: 0.7739 - val_loss: 0.0515 - val_accuracy: 0.6484
Epoch 78/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0334 - accuracy: 0.7759 - val_loss: 0.0523 - val_accuracy: 0.6418
Epoch 79/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0333 - accuracy: 0.7753 - val_loss: 0.0515 - val_accuracy: 0.6486
Epoch 80/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0332 - accuracy: 0.7763 - val_loss: 0.0517 - val_accuracy: 0.6470
Epoch 81/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0331 - accuracy: 0.7781 - val_loss: 0.0527 - val_accuracy: 0.6432
Epoch 82/200
1407/1407 [==============================] - 5s 4ms/step - loss: 0.0335 - accuracy: 0.7760 - val_loss: 0.0521 - val_accuracy: 0.6424
Epoch 83/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0332 - accuracy: 0.7757 - val_loss: 0.0519 - val_accuracy: 0.6478
Epoch 84/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0331 - accuracy: 0.7776 - val_loss: 0.0529 - val_accuracy: 0.6358
Epoch 85/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0332 - accuracy: 0.7773 - val_loss: 0.0518 - val_accuracy: 0.6432
Epoch 86/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0331 - accuracy: 0.7775 - val_loss: 0.0522 - val_accuracy: 0.6438
Epoch 87/200
1407/1407 [==============================] - 5s 4ms/step - loss: 0.0330 - accuracy: 0.7787 - val_loss: 0.0518 - val_accuracy: 0.6516
Epoch 88/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0329 - accuracy: 0.7793 - val_loss: 0.0523 - val_accuracy: 0.6486
Epoch 89/200
1407/1407 [==============================] - 5s 4ms/step - loss: 0.0329 - accuracy: 0.7801 - val_loss: 0.0527 - val_accuracy: 0.6440
Epoch 90/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0329 - accuracy: 0.7808 - val_loss: 0.0529 - val_accuracy: 0.6372
Epoch 91/200
1407/1407 [==============================] - 5s 4ms/step - loss: 0.0329 - accuracy: 0.7803 - val_loss: 0.0527 - val_accuracy: 0.6450
Epoch 92/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0329 - accuracy: 0.7802 - val_loss: 0.0518 - val_accuracy: 0.6488
Epoch 93/200
1407/1407 [==============================] - 5s 4ms/step - loss: 0.0329 - accuracy: 0.7799 - val_loss: 0.0527 - val_accuracy: 0.6418
Epoch 94/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0326 - accuracy: 0.7822 - val_loss: 0.0525 - val_accuracy: 0.6508
Epoch 95/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0329 - accuracy: 0.7807 - val_loss: 0.0539 - val_accuracy: 0.6306
Epoch 96/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0328 - accuracy: 0.7807 - val_loss: 0.0530 - val_accuracy: 0.6426
Epoch 97/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0326 - accuracy: 0.7832 - val_loss: 0.0527 - val_accuracy: 0.6434
Epoch 98/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0326 - accuracy: 0.7812 - val_loss: 0.0536 - val_accuracy: 0.6404
Epoch 99/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0325 - accuracy: 0.7857 - val_loss: 0.0531 - val_accuracy: 0.6436
Epoch 100/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0326 - accuracy: 0.7820 - val_loss: 0.0523 - val_accuracy: 0.6480
Epoch 101/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0326 - accuracy: 0.7826 - val_loss: 0.0525 - val_accuracy: 0.6434
Epoch 102/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0325 - accuracy: 0.7827 - val_loss: 0.0530 - val_accuracy: 0.6418
Epoch 103/200
1407/1407 [==============================] - 5s 4ms/step - loss: 0.0325 - accuracy: 0.7847 - val_loss: 0.0527 - val_accuracy: 0.6454
Epoch 104/200
1407/1407 [==============================] - 5s 4ms/step - loss: 0.0325 - accuracy: 0.7815 - val_loss: 0.0543 - val_accuracy: 0.6328
Epoch 105/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0323 - accuracy: 0.7854 - val_loss: 0.0533 - val_accuracy: 0.6382
Epoch 106/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0326 - accuracy: 0.7818 - val_loss: 0.0527 - val_accuracy: 0.6464
Epoch 107/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0323 - accuracy: 0.7850 - val_loss: 0.0533 - val_accuracy: 0.6406
Epoch 108/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0322 - accuracy: 0.7863 - val_loss: 0.0533 - val_accuracy: 0.6468
Epoch 109/200
1407/1407 [==============================] - 5s 4ms/step - loss: 0.0321 - accuracy: 0.7858 - val_loss: 0.0524 - val_accuracy: 0.6516
Epoch 110/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0322 - accuracy: 0.7862 - val_loss: 0.0524 - val_accuracy: 0.6474
Epoch 111/200
1407/1407 [==============================] - 5s 4ms/step - loss: 0.0323 - accuracy: 0.7852 - val_loss: 0.0533 - val_accuracy: 0.6458
Epoch 112/200
1407/1407 [==============================] - 5s 4ms/step - loss: 0.0322 - accuracy: 0.7864 - val_loss: 0.0529 - val_accuracy: 0.6474
Epoch 113/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0318 - accuracy: 0.7904 - val_loss: 0.0528 - val_accuracy: 0.6434
Epoch 114/200
1407/1407 [==============================] - 5s 4ms/step - loss: 0.0320 - accuracy: 0.7884 - val_loss: 0.0529 - val_accuracy: 0.6426
Epoch 115/200
1407/1407 [==============================] - 5s 4ms/step - loss: 0.0320 - accuracy: 0.7897 - val_loss: 0.0538 - val_accuracy: 0.6428
Epoch 116/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0320 - accuracy: 0.7881 - val_loss: 0.0531 - val_accuracy: 0.6424
Epoch 117/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0320 - accuracy: 0.7873 - val_loss: 0.0535 - val_accuracy: 0.6376
Epoch 118/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0319 - accuracy: 0.7899 - val_loss: 0.0544 - val_accuracy: 0.6344
Epoch 119/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0318 - accuracy: 0.7891 - val_loss: 0.0541 - val_accuracy: 0.6374
Epoch 120/200
1407/1407 [==============================] - 5s 4ms/step - loss: 0.0319 - accuracy: 0.7889 - val_loss: 0.0538 - val_accuracy: 0.6380
Epoch 121/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0317 - accuracy: 0.7905 - val_loss: 0.0539 - val_accuracy: 0.6442
Epoch 122/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0317 - accuracy: 0.7909 - val_loss: 0.0538 - val_accuracy: 0.6406
Epoch 123/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0317 - accuracy: 0.7914 - val_loss: 0.0535 - val_accuracy: 0.6412
Epoch 124/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0318 - accuracy: 0.7896 - val_loss: 0.0547 - val_accuracy: 0.6324
Epoch 125/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0317 - accuracy: 0.7916 - val_loss: 0.0539 - val_accuracy: 0.6402
Epoch 126/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0318 - accuracy: 0.7913 - val_loss: 0.0550 - val_accuracy: 0.6350
Epoch 127/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0318 - accuracy: 0.7904 - val_loss: 0.0544 - val_accuracy: 0.6384
Epoch 128/200
1407/1407 [==============================] - 5s 4ms/step - loss: 0.0316 - accuracy: 0.7918 - val_loss: 0.0543 - val_accuracy: 0.6412
Epoch 129/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0317 - accuracy: 0.7918 - val_loss: 0.0540 - val_accuracy: 0.6432
Epoch 130/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0317 - accuracy: 0.7913 - val_loss: 0.0537 - val_accuracy: 0.6462
Epoch 131/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0314 - accuracy: 0.7943 - val_loss: 0.0541 - val_accuracy: 0.6456
Epoch 132/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0314 - accuracy: 0.7939 - val_loss: 0.0548 - val_accuracy: 0.6394
Epoch 133/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0315 - accuracy: 0.7927 - val_loss: 0.0544 - val_accuracy: 0.6416
Epoch 134/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0315 - accuracy: 0.7929 - val_loss: 0.0549 - val_accuracy: 0.6410
Epoch 135/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0314 - accuracy: 0.7945 - val_loss: 0.0546 - val_accuracy: 0.6416
Epoch 136/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0316 - accuracy: 0.7928 - val_loss: 0.0537 - val_accuracy: 0.6408
Epoch 137/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0316 - accuracy: 0.7924 - val_loss: 0.0545 - val_accuracy: 0.6412
Epoch 138/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0314 - accuracy: 0.7951 - val_loss: 0.0561 - val_accuracy: 0.6322
Epoch 139/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0316 - accuracy: 0.7943 - val_loss: 0.0547 - val_accuracy: 0.6390
Epoch 140/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0313 - accuracy: 0.7950 - val_loss: 0.0548 - val_accuracy: 0.6440
Epoch 141/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0314 - accuracy: 0.7952 - val_loss: 0.0547 - val_accuracy: 0.6370
Epoch 142/200
1407/1407 [==============================] - 5s 4ms/step - loss: 0.0313 - accuracy: 0.7960 - val_loss: 0.0551 - val_accuracy: 0.6360
Epoch 143/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0312 - accuracy: 0.7958 - val_loss: 0.0554 - val_accuracy: 0.6364
Epoch 144/200
1407/1407 [==============================] - 5s 4ms/step - loss: 0.0314 - accuracy: 0.7950 - val_loss: 0.0547 - val_accuracy: 0.6414
Epoch 145/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0314 - accuracy: 0.7944 - val_loss: 0.0555 - val_accuracy: 0.6368
Epoch 146/200
1407/1407 [==============================] - 5s 4ms/step - loss: 0.0312 - accuracy: 0.7961 - val_loss: 0.0561 - val_accuracy: 0.6306
Epoch 147/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0313 - accuracy: 0.7961 - val_loss: 0.0545 - val_accuracy: 0.6430
Epoch 148/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0311 - accuracy: 0.7970 - val_loss: 0.0546 - val_accuracy: 0.6384
Epoch 149/200
1407/1407 [==============================] - 5s 4ms/step - loss: 0.0309 - accuracy: 0.7984 - val_loss: 0.0543 - val_accuracy: 0.6454
Epoch 150/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0317 - accuracy: 0.7929 - val_loss: 0.0545 - val_accuracy: 0.6452
Epoch 151/200
1407/1407 [==============================] - 5s 4ms/step - loss: 0.0311 - accuracy: 0.7978 - val_loss: 0.0553 - val_accuracy: 0.6382
Epoch 152/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0313 - accuracy: 0.7956 - val_loss: 0.0552 - val_accuracy: 0.6370
Epoch 153/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0310 - accuracy: 0.7968 - val_loss: 0.0548 - val_accuracy: 0.6404
Epoch 154/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0312 - accuracy: 0.7970 - val_loss: 0.0557 - val_accuracy: 0.6332
Epoch 155/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0311 - accuracy: 0.7975 - val_loss: 0.0545 - val_accuracy: 0.6410
Epoch 156/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0311 - accuracy: 0.7974 - val_loss: 0.0556 - val_accuracy: 0.6390
Epoch 157/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0311 - accuracy: 0.7973 - val_loss: 0.0549 - val_accuracy: 0.6444
Epoch 158/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0312 - accuracy: 0.7962 - val_loss: 0.0556 - val_accuracy: 0.6362
Epoch 159/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0310 - accuracy: 0.7979 - val_loss: 0.0571 - val_accuracy: 0.6310
Epoch 160/200
1407/1407 [==============================] - 5s 4ms/step - loss: 0.0310 - accuracy: 0.7984 - val_loss: 0.0553 - val_accuracy: 0.6408
Epoch 161/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0310 - accuracy: 0.7972 - val_loss: 0.0549 - val_accuracy: 0.6436
Epoch 162/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0312 - accuracy: 0.7965 - val_loss: 0.0549 - val_accuracy: 0.6444
Epoch 163/200
1407/1407 [==============================] - 5s 4ms/step - loss: 0.0311 - accuracy: 0.7973 - val_loss: 0.0553 - val_accuracy: 0.6444
Epoch 164/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0308 - accuracy: 0.8003 - val_loss: 0.0550 - val_accuracy: 0.6406
Epoch 165/200
1407/1407 [==============================] - 5s 4ms/step - loss: 0.0309 - accuracy: 0.7999 - val_loss: 0.0552 - val_accuracy: 0.6402
Epoch 166/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0311 - accuracy: 0.7984 - val_loss: 0.0544 - val_accuracy: 0.6480
Epoch 167/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0308 - accuracy: 0.8004 - val_loss: 0.0553 - val_accuracy: 0.6422
Epoch 168/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0311 - accuracy: 0.7979 - val_loss: 0.0559 - val_accuracy: 0.6396
Epoch 169/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0307 - accuracy: 0.8001 - val_loss: 0.0551 - val_accuracy: 0.6418
Epoch 170/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0308 - accuracy: 0.8004 - val_loss: 0.0559 - val_accuracy: 0.6366
Epoch 171/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0308 - accuracy: 0.7997 - val_loss: 0.0551 - val_accuracy: 0.6444
Epoch 172/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0308 - accuracy: 0.8009 - val_loss: 0.0549 - val_accuracy: 0.6424
Epoch 173/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0307 - accuracy: 0.8021 - val_loss: 0.0567 - val_accuracy: 0.6328
Epoch 174/200
1407/1407 [==============================] - 5s 4ms/step - loss: 0.0309 - accuracy: 0.8003 - val_loss: 0.0579 - val_accuracy: 0.6246
Epoch 175/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0307 - accuracy: 0.8012 - val_loss: 0.0550 - val_accuracy: 0.6430
Epoch 176/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0307 - accuracy: 0.8022 - val_loss: 0.0563 - val_accuracy: 0.6392
Epoch 177/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0308 - accuracy: 0.8001 - val_loss: 0.0550 - val_accuracy: 0.6464
Epoch 178/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0309 - accuracy: 0.8009 - val_loss: 0.0570 - val_accuracy: 0.6296
Epoch 179/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0306 - accuracy: 0.8019 - val_loss: 0.0563 - val_accuracy: 0.6354
Epoch 180/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0307 - accuracy: 0.8020 - val_loss: 0.0568 - val_accuracy: 0.6350
Epoch 181/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0306 - accuracy: 0.8012 - val_loss: 0.0555 - val_accuracy: 0.6394
Epoch 182/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0308 - accuracy: 0.8013 - val_loss: 0.0568 - val_accuracy: 0.6340
Epoch 183/200
1407/1407 [==============================] - 5s 4ms/step - loss: 0.0306 - accuracy: 0.8022 - val_loss: 0.0566 - val_accuracy: 0.6356
Epoch 184/200
1407/1407 [==============================] - 5s 4ms/step - loss: 0.0307 - accuracy: 0.8018 - val_loss: 0.0562 - val_accuracy: 0.6382
Epoch 185/200
1407/1407 [==============================] - 5s 4ms/step - loss: 0.0307 - accuracy: 0.8012 - val_loss: 0.0563 - val_accuracy: 0.6376
Epoch 186/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0304 - accuracy: 0.8034 - val_loss: 0.0564 - val_accuracy: 0.6420
Epoch 187/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0305 - accuracy: 0.8023 - val_loss: 0.0562 - val_accuracy: 0.6372
Epoch 188/200
1407/1407 [==============================] - 5s 4ms/step - loss: 0.0308 - accuracy: 0.8011 - val_loss: 0.0562 - val_accuracy: 0.6390
Epoch 189/200
1407/1407 [==============================] - 5s 4ms/step - loss: 0.0308 - accuracy: 0.8016 - val_loss: 0.0568 - val_accuracy: 0.6352
Epoch 190/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0305 - accuracy: 0.8036 - val_loss: 0.0571 - val_accuracy: 0.6348
Epoch 191/200
1407/1407 [==============================] - 5s 4ms/step - loss: 0.0305 - accuracy: 0.8042 - val_loss: 0.0558 - val_accuracy: 0.6460
Epoch 192/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0306 - accuracy: 0.8030 - val_loss: 0.0563 - val_accuracy: 0.6400
Epoch 193/200
1407/1407 [==============================] - 5s 4ms/step - loss: 0.0308 - accuracy: 0.8027 - val_loss: 0.0558 - val_accuracy: 0.6456
Epoch 194/200
1407/1407 [==============================] - 5s 4ms/step - loss: 0.0307 - accuracy: 0.8026 - val_loss: 0.0566 - val_accuracy: 0.6348
Epoch 195/200
1407/1407 [==============================] - 5s 4ms/step - loss: 0.0305 - accuracy: 0.8037 - val_loss: 0.0567 - val_accuracy: 0.6380
Epoch 196/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0303 - accuracy: 0.8058 - val_loss: 0.0564 - val_accuracy: 0.6426
Epoch 197/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0306 - accuracy: 0.8017 - val_loss: 0.0553 - val_accuracy: 0.6446
Epoch 198/200
1407/1407 [==============================] - 6s 4ms/step - loss: 0.0307 - accuracy: 0.8022 - val_loss: 0.0554 - val_accuracy: 0.6428
Epoch 199/200
1407/1407 [==============================] - 5s 4ms/step - loss: 0.0304 - accuracy: 0.8048 - val_loss: 0.0572 - val_accuracy: 0.6348
Epoch 200/200
1407/1407 [==============================] - 5s 4ms/step - loss: 0.0304 - accuracy: 0.8049 - val_loss: 0.0565 - val_accuracy: 0.6370
In [ ]:
# #write accuracies in a csv file
import pandas as pd
data = {'Epoch': list(range(1, len(history_baseline.history['val_accuracy']) + 1)),
        'Train Accuracy' : history_baseline.history['accuracy'] ,
        'Test Accuracy': history_baseline.history['val_accuracy']}
df = pd.DataFrame(data)

#folder = '/content/gdrive/MyDrive/DLS-codes/HW2/csv/'
folder = '/kaggle/working/'
csv_filename = 'baseline.csv'
df.to_csv(folder + csv_filename, index=False)

b. Data Augmentation.

In [ ]:
from keras.datasets import cifar10
import keras
import tensorflow as tf
import numpy as np
from tensorflow.keras.layers import Conv2D, MaxPooling2D, Dense, Flatten, Dropout
from tensorflow.keras.models import Sequential
import os

/opt/conda/lib/python3.10/site-packages/scipy/__init__.py:146: UserWarning: A NumPy version >=1.16.5 and <1.23.0 is required for this version of SciPy (detected version 1.23.5
  warnings.warn(f"A NumPy version >={np_minversion} and <{np_maxversion}"
/opt/conda/lib/python3.10/site-packages/tensorflow_io/python/ops/__init__.py:98: UserWarning: unable to load libtensorflow_io_plugins.so: unable to open file: libtensorflow_io_plugins.so, from paths: ['/opt/conda/lib/python3.10/site-packages/tensorflow_io/python/ops/libtensorflow_io_plugins.so']
caused by: ['/opt/conda/lib/python3.10/site-packages/tensorflow_io/python/ops/libtensorflow_io_plugins.so: undefined symbol: _ZN3tsl6StatusC1EN10tensorflow5error4CodeESt17basic_string_viewIcSt11char_traitsIcEENS_14SourceLocationE']
  warnings.warn(f"unable to load libtensorflow_io_plugins.so: {e}")
/opt/conda/lib/python3.10/site-packages/tensorflow_io/python/ops/__init__.py:104: UserWarning: file system plugins are not loaded: unable to open file: libtensorflow_io.so, from paths: ['/opt/conda/lib/python3.10/site-packages/tensorflow_io/python/ops/libtensorflow_io.so']
caused by: ['/opt/conda/lib/python3.10/site-packages/tensorflow_io/python/ops/libtensorflow_io.so: undefined symbol: _ZTVN10tensorflow13GcsFileSystemE']
  warnings.warn(f"file system plugins are not loaded: {e}")
In [ ]:
(x_train, y_train), (x_test, y_test) = cifar10.load_data()
In [ ]:
#set aside 5000 examples for validation
x_val = x_train[-5000:]
y_val = y_train[-5000:]
x_train = x_train[:-5000]
y_train = y_train[:-5000]
In [ ]:
#reshape to 32x32x3
x_train = x_train.reshape(x_train.shape[0] , 32, 32, 3)
x_test = x_test.reshape(x_test.shape[0], 32, 32, 3)
x_val = x_val.reshape(x_val.shape[0], 32, 32, 3)
In [ ]:
x_train = x_train.astype('float32')
x_test = y_test.astype('float32')
x_val = x_val.astype('float32')
In [ ]:
#normalize to -1 to 1
x_train = x_train/255.0
x_val = x_val/255.0
In [ ]:
#dataset1: brighten every pixel by 10%
data1 = np.minimum(1.1 * x_train , 1)
#darken every pixel by 10%
data2 = np.maximum(0.9 * x_train, 0)
#flip all imagges horizontally
data3 = np.fliplr(x_train)
#original dataset : x_train
#data4 = x_train.copy()
In [ ]:
#combine the 4 datatset
x_train_aug = np.concatenate([data1, data2, data3, x_train], axis = 0)
y_train_aug = np.concatenate([y_train, y_train, y_train, y_train], axis = 0)
In [ ]:
x_train_aug = x_train_aug * 2 - 1
x_val = x_val * 2 - 1
In [ ]:
x_train_aug.shape , y_train_aug.shape
Out[ ]:
((180000, 32, 32, 3), (180000, 1))
In [ ]:
#categorical
y_train_aug = keras.utils.to_categorical(y_train_aug, num_classes = 10)
y_val = keras.utils.to_categorical(y_val, num_classes = 10)
In [ ]:
#model
model = Sequential()
model.add(Conv2D(filters = 10, kernel_size = (5, 5) , strides = (1, 1), padding = "same",input_shape = (32,32,3),
                 activation = "relu", kernel_initializer = "he_normal"))
model.add(MaxPooling2D(pool_size = (2, 2), strides = (2, 2)))
model.add(Conv2D(filters = 10, kernel_size = (5, 5) , strides = (1, 1), padding = "same",
                 activation = "relu", kernel_initializer = "he_normal"))
model.add(MaxPooling2D(pool_size = (2, 2), strides = (2, 2)))
model.add(Flatten())
model.add(Dense(20, activation = "relu", kernel_initializer = "he_normal"))
model.add(Dense(10, activation = "softmax"))
In [ ]:
model.summary()

Model: "sequential_3"
_________________________________________________________________
 Layer (type)                Output Shape              Param #   
=================================================================
 conv2d_6 (Conv2D)           (None, 32, 32, 10)        760       
                                                                 
 max_pooling2d_6 (MaxPooling  (None, 16, 16, 10)       0         
 2D)                                                             
                                                                 
 conv2d_7 (Conv2D)           (None, 16, 16, 10)        2510      
                                                                 
 max_pooling2d_7 (MaxPooling  (None, 8, 8, 10)         0         
 2D)                                                             
                                                                 
 flatten_3 (Flatten)         (None, 640)               0         
                                                                 
 dense_6 (Dense)             (None, 20)                12820     
                                                                 
 dense_7 (Dense)             (None, 10)                210       
                                                                 
=================================================================
Total params: 16,300
Trainable params: 16,300
Non-trainable params: 0
_________________________________________________________________
In [ ]:
model.compile(optimizer = "Adam", loss = "mse", metrics = ["accuracy"])
history_aug = model.fit(x_train_aug, y_train_aug, epochs = 200, batch_size = 32, validation_data = (x_val, y_val))

Epoch 1/200
5625/5625 [==============================] - 20s 3ms/step - loss: 0.0658 - accuracy: 0.4735 - val_loss: 0.0546 - val_accuracy: 0.5830
Epoch 2/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0556 - accuracy: 0.5758 - val_loss: 0.0499 - val_accuracy: 0.6286
Epoch 3/200
5625/5625 [==============================] - 18s 3ms/step - loss: 0.0524 - accuracy: 0.6061 - val_loss: 0.0498 - val_accuracy: 0.6332
Epoch 4/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0506 - accuracy: 0.6219 - val_loss: 0.0490 - val_accuracy: 0.6370
Epoch 5/200
5625/5625 [==============================] - 18s 3ms/step - loss: 0.0493 - accuracy: 0.6343 - val_loss: 0.0498 - val_accuracy: 0.6368
Epoch 6/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0484 - accuracy: 0.6416 - val_loss: 0.0477 - val_accuracy: 0.6570
Epoch 7/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0476 - accuracy: 0.6488 - val_loss: 0.0481 - val_accuracy: 0.6464
Epoch 8/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0470 - accuracy: 0.6545 - val_loss: 0.0472 - val_accuracy: 0.6576
Epoch 9/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0465 - accuracy: 0.6588 - val_loss: 0.0484 - val_accuracy: 0.6460
Epoch 10/200
5625/5625 [==============================] - 18s 3ms/step - loss: 0.0460 - accuracy: 0.6645 - val_loss: 0.0488 - val_accuracy: 0.6408
Epoch 11/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0456 - accuracy: 0.6676 - val_loss: 0.0469 - val_accuracy: 0.6604
Epoch 12/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0453 - accuracy: 0.6693 - val_loss: 0.0471 - val_accuracy: 0.6558
Epoch 13/200
5625/5625 [==============================] - 18s 3ms/step - loss: 0.0450 - accuracy: 0.6730 - val_loss: 0.0470 - val_accuracy: 0.6534
Epoch 14/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0447 - accuracy: 0.6752 - val_loss: 0.0478 - val_accuracy: 0.6534
Epoch 15/200
5625/5625 [==============================] - 18s 3ms/step - loss: 0.0444 - accuracy: 0.6788 - val_loss: 0.0464 - val_accuracy: 0.6608
Epoch 16/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0441 - accuracy: 0.6810 - val_loss: 0.0466 - val_accuracy: 0.6630
Epoch 17/200
5625/5625 [==============================] - 18s 3ms/step - loss: 0.0440 - accuracy: 0.6820 - val_loss: 0.0463 - val_accuracy: 0.6606
Epoch 18/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0438 - accuracy: 0.6836 - val_loss: 0.0460 - val_accuracy: 0.6670
Epoch 19/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0435 - accuracy: 0.6863 - val_loss: 0.0464 - val_accuracy: 0.6642
Epoch 20/200
5625/5625 [==============================] - 18s 3ms/step - loss: 0.0434 - accuracy: 0.6867 - val_loss: 0.0457 - val_accuracy: 0.6696
Epoch 21/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0432 - accuracy: 0.6888 - val_loss: 0.0478 - val_accuracy: 0.6538
Epoch 22/200
5625/5625 [==============================] - 18s 3ms/step - loss: 0.0431 - accuracy: 0.6893 - val_loss: 0.0464 - val_accuracy: 0.6624
Epoch 23/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0430 - accuracy: 0.6907 - val_loss: 0.0465 - val_accuracy: 0.6664
Epoch 24/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0427 - accuracy: 0.6930 - val_loss: 0.0471 - val_accuracy: 0.6586
Epoch 25/200
5625/5625 [==============================] - 18s 3ms/step - loss: 0.0427 - accuracy: 0.6933 - val_loss: 0.0464 - val_accuracy: 0.6620
Epoch 26/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0426 - accuracy: 0.6948 - val_loss: 0.0472 - val_accuracy: 0.6598
Epoch 27/200
5625/5625 [==============================] - 18s 3ms/step - loss: 0.0425 - accuracy: 0.6949 - val_loss: 0.0472 - val_accuracy: 0.6608
Epoch 28/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0424 - accuracy: 0.6965 - val_loss: 0.0469 - val_accuracy: 0.6564
Epoch 29/200
5625/5625 [==============================] - 18s 3ms/step - loss: 0.0423 - accuracy: 0.6978 - val_loss: 0.0469 - val_accuracy: 0.6626
Epoch 30/200
5625/5625 [==============================] - 18s 3ms/step - loss: 0.0422 - accuracy: 0.6981 - val_loss: 0.0467 - val_accuracy: 0.6602
Epoch 31/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0421 - accuracy: 0.6987 - val_loss: 0.0470 - val_accuracy: 0.6600
Epoch 32/200
5625/5625 [==============================] - 18s 3ms/step - loss: 0.0420 - accuracy: 0.6998 - val_loss: 0.0472 - val_accuracy: 0.6644
Epoch 33/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0420 - accuracy: 0.7003 - val_loss: 0.0467 - val_accuracy: 0.6630
Epoch 34/200
5625/5625 [==============================] - 18s 3ms/step - loss: 0.0419 - accuracy: 0.7009 - val_loss: 0.0471 - val_accuracy: 0.6624
Epoch 35/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0418 - accuracy: 0.7009 - val_loss: 0.0474 - val_accuracy: 0.6598
Epoch 36/200
5625/5625 [==============================] - 18s 3ms/step - loss: 0.0419 - accuracy: 0.7011 - val_loss: 0.0473 - val_accuracy: 0.6576
Epoch 37/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0417 - accuracy: 0.7025 - val_loss: 0.0479 - val_accuracy: 0.6576
Epoch 38/200
5625/5625 [==============================] - 18s 3ms/step - loss: 0.0417 - accuracy: 0.7034 - val_loss: 0.0475 - val_accuracy: 0.6582
Epoch 39/200
5625/5625 [==============================] - 18s 3ms/step - loss: 0.0417 - accuracy: 0.7034 - val_loss: 0.0471 - val_accuracy: 0.6614
Epoch 40/200
5625/5625 [==============================] - 18s 3ms/step - loss: 0.0415 - accuracy: 0.7042 - val_loss: 0.0463 - val_accuracy: 0.6720
Epoch 41/200
5625/5625 [==============================] - 18s 3ms/step - loss: 0.0415 - accuracy: 0.7051 - val_loss: 0.0475 - val_accuracy: 0.6630
Epoch 42/200
5625/5625 [==============================] - 18s 3ms/step - loss: 0.0415 - accuracy: 0.7052 - val_loss: 0.0476 - val_accuracy: 0.6598
Epoch 43/200
5625/5625 [==============================] - 18s 3ms/step - loss: 0.0415 - accuracy: 0.7050 - val_loss: 0.0475 - val_accuracy: 0.6586
Epoch 44/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0414 - accuracy: 0.7062 - val_loss: 0.0471 - val_accuracy: 0.6638
Epoch 45/200
5625/5625 [==============================] - 18s 3ms/step - loss: 0.0414 - accuracy: 0.7059 - val_loss: 0.0479 - val_accuracy: 0.6616
Epoch 46/200
5625/5625 [==============================] - 18s 3ms/step - loss: 0.0413 - accuracy: 0.7074 - val_loss: 0.0476 - val_accuracy: 0.6602
Epoch 47/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0412 - accuracy: 0.7070 - val_loss: 0.0474 - val_accuracy: 0.6650
Epoch 48/200
5625/5625 [==============================] - 18s 3ms/step - loss: 0.0412 - accuracy: 0.7075 - val_loss: 0.0491 - val_accuracy: 0.6544
Epoch 49/200
5625/5625 [==============================] - 18s 3ms/step - loss: 0.0411 - accuracy: 0.7083 - val_loss: 0.0477 - val_accuracy: 0.6606
Epoch 50/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0412 - accuracy: 0.7079 - val_loss: 0.0485 - val_accuracy: 0.6564
Epoch 51/200
5625/5625 [==============================] - 18s 3ms/step - loss: 0.0412 - accuracy: 0.7083 - val_loss: 0.0478 - val_accuracy: 0.6584
Epoch 52/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0410 - accuracy: 0.7089 - val_loss: 0.0484 - val_accuracy: 0.6590
Epoch 53/200
5625/5625 [==============================] - 18s 3ms/step - loss: 0.0411 - accuracy: 0.7087 - val_loss: 0.0475 - val_accuracy: 0.6674
Epoch 54/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0410 - accuracy: 0.7096 - val_loss: 0.0481 - val_accuracy: 0.6604
Epoch 55/200
5625/5625 [==============================] - 18s 3ms/step - loss: 0.0409 - accuracy: 0.7105 - val_loss: 0.0471 - val_accuracy: 0.6666
Epoch 56/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0409 - accuracy: 0.7103 - val_loss: 0.0480 - val_accuracy: 0.6588
Epoch 57/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0408 - accuracy: 0.7108 - val_loss: 0.0478 - val_accuracy: 0.6634
Epoch 58/200
5625/5625 [==============================] - 18s 3ms/step - loss: 0.0409 - accuracy: 0.7107 - val_loss: 0.0480 - val_accuracy: 0.6582
Epoch 59/200
5625/5625 [==============================] - 18s 3ms/step - loss: 0.0409 - accuracy: 0.7105 - val_loss: 0.0474 - val_accuracy: 0.6670
Epoch 60/200
5625/5625 [==============================] - 18s 3ms/step - loss: 0.0408 - accuracy: 0.7121 - val_loss: 0.0478 - val_accuracy: 0.6574
Epoch 61/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0408 - accuracy: 0.7110 - val_loss: 0.0477 - val_accuracy: 0.6630
Epoch 62/200
5625/5625 [==============================] - 18s 3ms/step - loss: 0.0407 - accuracy: 0.7128 - val_loss: 0.0479 - val_accuracy: 0.6612
Epoch 63/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0407 - accuracy: 0.7124 - val_loss: 0.0481 - val_accuracy: 0.6570
Epoch 64/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0407 - accuracy: 0.7127 - val_loss: 0.0475 - val_accuracy: 0.6666
Epoch 65/200
5625/5625 [==============================] - 18s 3ms/step - loss: 0.0406 - accuracy: 0.7134 - val_loss: 0.0484 - val_accuracy: 0.6598
Epoch 66/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0407 - accuracy: 0.7125 - val_loss: 0.0491 - val_accuracy: 0.6482
Epoch 67/200
5625/5625 [==============================] - 18s 3ms/step - loss: 0.0406 - accuracy: 0.7135 - val_loss: 0.0487 - val_accuracy: 0.6604
Epoch 68/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0406 - accuracy: 0.7140 - val_loss: 0.0481 - val_accuracy: 0.6642
Epoch 69/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0405 - accuracy: 0.7146 - val_loss: 0.0487 - val_accuracy: 0.6550
Epoch 70/200
5625/5625 [==============================] - 18s 3ms/step - loss: 0.0405 - accuracy: 0.7144 - val_loss: 0.0483 - val_accuracy: 0.6600
Epoch 71/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0405 - accuracy: 0.7151 - val_loss: 0.0488 - val_accuracy: 0.6538
Epoch 72/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0405 - accuracy: 0.7146 - val_loss: 0.0476 - val_accuracy: 0.6644
Epoch 73/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0404 - accuracy: 0.7153 - val_loss: 0.0484 - val_accuracy: 0.6596
Epoch 74/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0405 - accuracy: 0.7153 - val_loss: 0.0487 - val_accuracy: 0.6534
Epoch 75/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0405 - accuracy: 0.7153 - val_loss: 0.0483 - val_accuracy: 0.6600
Epoch 76/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0404 - accuracy: 0.7149 - val_loss: 0.0496 - val_accuracy: 0.6512
Epoch 77/200
5625/5625 [==============================] - 18s 3ms/step - loss: 0.0404 - accuracy: 0.7153 - val_loss: 0.0485 - val_accuracy: 0.6534
Epoch 78/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0404 - accuracy: 0.7157 - val_loss: 0.0497 - val_accuracy: 0.6500
Epoch 79/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0403 - accuracy: 0.7169 - val_loss: 0.0483 - val_accuracy: 0.6580
Epoch 80/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0403 - accuracy: 0.7169 - val_loss: 0.0487 - val_accuracy: 0.6548
Epoch 81/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0403 - accuracy: 0.7174 - val_loss: 0.0498 - val_accuracy: 0.6470
Epoch 82/200
5625/5625 [==============================] - 18s 3ms/step - loss: 0.0403 - accuracy: 0.7175 - val_loss: 0.0489 - val_accuracy: 0.6546
Epoch 83/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0403 - accuracy: 0.7168 - val_loss: 0.0485 - val_accuracy: 0.6574
Epoch 84/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0403 - accuracy: 0.7173 - val_loss: 0.0491 - val_accuracy: 0.6534
Epoch 85/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0402 - accuracy: 0.7171 - val_loss: 0.0487 - val_accuracy: 0.6612
Epoch 86/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0402 - accuracy: 0.7169 - val_loss: 0.0489 - val_accuracy: 0.6594
Epoch 87/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0402 - accuracy: 0.7180 - val_loss: 0.0489 - val_accuracy: 0.6576
Epoch 88/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0401 - accuracy: 0.7184 - val_loss: 0.0484 - val_accuracy: 0.6648
Epoch 89/200
5625/5625 [==============================] - 18s 3ms/step - loss: 0.0401 - accuracy: 0.7180 - val_loss: 0.0486 - val_accuracy: 0.6568
Epoch 90/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0401 - accuracy: 0.7184 - val_loss: 0.0491 - val_accuracy: 0.6568
Epoch 91/200
5625/5625 [==============================] - 18s 3ms/step - loss: 0.0401 - accuracy: 0.7194 - val_loss: 0.0483 - val_accuracy: 0.6584
Epoch 92/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0402 - accuracy: 0.7184 - val_loss: 0.0498 - val_accuracy: 0.6482
Epoch 93/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0401 - accuracy: 0.7193 - val_loss: 0.0484 - val_accuracy: 0.6602
Epoch 94/200
5625/5625 [==============================] - 18s 3ms/step - loss: 0.0400 - accuracy: 0.7188 - val_loss: 0.0483 - val_accuracy: 0.6658
Epoch 95/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0401 - accuracy: 0.7190 - val_loss: 0.0481 - val_accuracy: 0.6586
Epoch 96/200
5625/5625 [==============================] - 18s 3ms/step - loss: 0.0400 - accuracy: 0.7199 - val_loss: 0.0501 - val_accuracy: 0.6474
Epoch 97/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0401 - accuracy: 0.7193 - val_loss: 0.0491 - val_accuracy: 0.6540
Epoch 98/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0400 - accuracy: 0.7199 - val_loss: 0.0480 - val_accuracy: 0.6630
Epoch 99/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0400 - accuracy: 0.7195 - val_loss: 0.0485 - val_accuracy: 0.6564
Epoch 100/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0399 - accuracy: 0.7203 - val_loss: 0.0497 - val_accuracy: 0.6480
Epoch 101/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0400 - accuracy: 0.7203 - val_loss: 0.0492 - val_accuracy: 0.6504
Epoch 102/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0399 - accuracy: 0.7211 - val_loss: 0.0487 - val_accuracy: 0.6588
Epoch 103/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0399 - accuracy: 0.7205 - val_loss: 0.0481 - val_accuracy: 0.6620
Epoch 104/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0399 - accuracy: 0.7216 - val_loss: 0.0484 - val_accuracy: 0.6580
Epoch 105/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0399 - accuracy: 0.7217 - val_loss: 0.0498 - val_accuracy: 0.6538
Epoch 106/200
5625/5625 [==============================] - 18s 3ms/step - loss: 0.0399 - accuracy: 0.7205 - val_loss: 0.0485 - val_accuracy: 0.6566
Epoch 107/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0398 - accuracy: 0.7222 - val_loss: 0.0494 - val_accuracy: 0.6486
Epoch 108/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0398 - accuracy: 0.7215 - val_loss: 0.0491 - val_accuracy: 0.6556
Epoch 109/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0398 - accuracy: 0.7215 - val_loss: 0.0500 - val_accuracy: 0.6476
Epoch 110/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0398 - accuracy: 0.7217 - val_loss: 0.0496 - val_accuracy: 0.6540
Epoch 111/200
5625/5625 [==============================] - 18s 3ms/step - loss: 0.0398 - accuracy: 0.7215 - val_loss: 0.0489 - val_accuracy: 0.6600
Epoch 112/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0398 - accuracy: 0.7218 - val_loss: 0.0497 - val_accuracy: 0.6512
Epoch 113/200
5625/5625 [==============================] - 18s 3ms/step - loss: 0.0398 - accuracy: 0.7221 - val_loss: 0.0487 - val_accuracy: 0.6560
Epoch 114/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0398 - accuracy: 0.7212 - val_loss: 0.0496 - val_accuracy: 0.6524
Epoch 115/200
5625/5625 [==============================] - 18s 3ms/step - loss: 0.0398 - accuracy: 0.7212 - val_loss: 0.0496 - val_accuracy: 0.6574
Epoch 116/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0398 - accuracy: 0.7217 - val_loss: 0.0492 - val_accuracy: 0.6546
Epoch 117/200
5625/5625 [==============================] - 18s 3ms/step - loss: 0.0398 - accuracy: 0.7224 - val_loss: 0.0493 - val_accuracy: 0.6568
Epoch 118/200
5625/5625 [==============================] - 18s 3ms/step - loss: 0.0398 - accuracy: 0.7220 - val_loss: 0.0482 - val_accuracy: 0.6650
Epoch 119/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0397 - accuracy: 0.7234 - val_loss: 0.0493 - val_accuracy: 0.6496
Epoch 120/200
5625/5625 [==============================] - 18s 3ms/step - loss: 0.0398 - accuracy: 0.7222 - val_loss: 0.0496 - val_accuracy: 0.6496
Epoch 121/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0397 - accuracy: 0.7216 - val_loss: 0.0488 - val_accuracy: 0.6522
Epoch 122/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0397 - accuracy: 0.7233 - val_loss: 0.0489 - val_accuracy: 0.6584
Epoch 123/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0397 - accuracy: 0.7224 - val_loss: 0.0494 - val_accuracy: 0.6536
Epoch 124/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0397 - accuracy: 0.7234 - val_loss: 0.0494 - val_accuracy: 0.6484
Epoch 125/200
5625/5625 [==============================] - 18s 3ms/step - loss: 0.0396 - accuracy: 0.7236 - val_loss: 0.0497 - val_accuracy: 0.6446
Epoch 126/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0397 - accuracy: 0.7234 - val_loss: 0.0489 - val_accuracy: 0.6528
Epoch 127/200
5625/5625 [==============================] - 18s 3ms/step - loss: 0.0397 - accuracy: 0.7223 - val_loss: 0.0494 - val_accuracy: 0.6560
Epoch 128/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0396 - accuracy: 0.7236 - val_loss: 0.0489 - val_accuracy: 0.6560
Epoch 129/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0395 - accuracy: 0.7240 - val_loss: 0.0491 - val_accuracy: 0.6522
Epoch 130/200
5625/5625 [==============================] - 18s 3ms/step - loss: 0.0396 - accuracy: 0.7246 - val_loss: 0.0491 - val_accuracy: 0.6530
Epoch 131/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0396 - accuracy: 0.7242 - val_loss: 0.0496 - val_accuracy: 0.6504
Epoch 132/200
5625/5625 [==============================] - 18s 3ms/step - loss: 0.0395 - accuracy: 0.7242 - val_loss: 0.0524 - val_accuracy: 0.6314
Epoch 133/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0396 - accuracy: 0.7240 - val_loss: 0.0489 - val_accuracy: 0.6574
Epoch 134/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0396 - accuracy: 0.7242 - val_loss: 0.0499 - val_accuracy: 0.6474
Epoch 135/200
5625/5625 [==============================] - 18s 3ms/step - loss: 0.0396 - accuracy: 0.7240 - val_loss: 0.0511 - val_accuracy: 0.6406
Epoch 136/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0396 - accuracy: 0.7238 - val_loss: 0.0497 - val_accuracy: 0.6540
Epoch 137/200
5625/5625 [==============================] - 18s 3ms/step - loss: 0.0395 - accuracy: 0.7250 - val_loss: 0.0501 - val_accuracy: 0.6468
Epoch 138/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0395 - accuracy: 0.7249 - val_loss: 0.0510 - val_accuracy: 0.6470
Epoch 139/200
5625/5625 [==============================] - 18s 3ms/step - loss: 0.0395 - accuracy: 0.7244 - val_loss: 0.0494 - val_accuracy: 0.6528
Epoch 140/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0395 - accuracy: 0.7246 - val_loss: 0.0502 - val_accuracy: 0.6470
Epoch 141/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0395 - accuracy: 0.7254 - val_loss: 0.0515 - val_accuracy: 0.6350
Epoch 142/200
5625/5625 [==============================] - 18s 3ms/step - loss: 0.0395 - accuracy: 0.7252 - val_loss: 0.0503 - val_accuracy: 0.6502
Epoch 143/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0395 - accuracy: 0.7252 - val_loss: 0.0498 - val_accuracy: 0.6478
Epoch 144/200
5625/5625 [==============================] - 18s 3ms/step - loss: 0.0395 - accuracy: 0.7256 - val_loss: 0.0493 - val_accuracy: 0.6512
Epoch 145/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0395 - accuracy: 0.7246 - val_loss: 0.0492 - val_accuracy: 0.6590
Epoch 146/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0395 - accuracy: 0.7252 - val_loss: 0.0491 - val_accuracy: 0.6526
Epoch 147/200
5625/5625 [==============================] - 18s 3ms/step - loss: 0.0395 - accuracy: 0.7252 - val_loss: 0.0494 - val_accuracy: 0.6530
Epoch 148/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0395 - accuracy: 0.7250 - val_loss: 0.0491 - val_accuracy: 0.6548
Epoch 149/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0394 - accuracy: 0.7257 - val_loss: 0.0504 - val_accuracy: 0.6480
Epoch 150/200
5625/5625 [==============================] - 20s 3ms/step - loss: 0.0394 - accuracy: 0.7258 - val_loss: 0.0491 - val_accuracy: 0.6540
Epoch 151/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0395 - accuracy: 0.7252 - val_loss: 0.0513 - val_accuracy: 0.6446
Epoch 152/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0394 - accuracy: 0.7267 - val_loss: 0.0505 - val_accuracy: 0.6460
Epoch 153/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0395 - accuracy: 0.7255 - val_loss: 0.0493 - val_accuracy: 0.6556
Epoch 154/200
5625/5625 [==============================] - 18s 3ms/step - loss: 0.0394 - accuracy: 0.7256 - val_loss: 0.0494 - val_accuracy: 0.6520
Epoch 155/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0393 - accuracy: 0.7270 - val_loss: 0.0505 - val_accuracy: 0.6456
Epoch 156/200
5625/5625 [==============================] - 18s 3ms/step - loss: 0.0393 - accuracy: 0.7265 - val_loss: 0.0513 - val_accuracy: 0.6382
Epoch 157/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0393 - accuracy: 0.7273 - val_loss: 0.0501 - val_accuracy: 0.6472
Epoch 158/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0393 - accuracy: 0.7269 - val_loss: 0.0499 - val_accuracy: 0.6508
Epoch 159/200
5625/5625 [==============================] - 18s 3ms/step - loss: 0.0394 - accuracy: 0.7265 - val_loss: 0.0494 - val_accuracy: 0.6512
Epoch 160/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0393 - accuracy: 0.7273 - val_loss: 0.0492 - val_accuracy: 0.6562
Epoch 161/200
5625/5625 [==============================] - 18s 3ms/step - loss: 0.0393 - accuracy: 0.7261 - val_loss: 0.0501 - val_accuracy: 0.6516
Epoch 162/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0393 - accuracy: 0.7264 - val_loss: 0.0501 - val_accuracy: 0.6450
Epoch 163/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0393 - accuracy: 0.7267 - val_loss: 0.0505 - val_accuracy: 0.6532
Epoch 164/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0393 - accuracy: 0.7276 - val_loss: 0.0511 - val_accuracy: 0.6430
Epoch 165/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0393 - accuracy: 0.7272 - val_loss: 0.0497 - val_accuracy: 0.6548
Epoch 166/200
5625/5625 [==============================] - 18s 3ms/step - loss: 0.0393 - accuracy: 0.7269 - val_loss: 0.0497 - val_accuracy: 0.6544
Epoch 167/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0392 - accuracy: 0.7279 - val_loss: 0.0495 - val_accuracy: 0.6550
Epoch 168/200
5625/5625 [==============================] - 18s 3ms/step - loss: 0.0393 - accuracy: 0.7271 - val_loss: 0.0502 - val_accuracy: 0.6496
Epoch 169/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0393 - accuracy: 0.7276 - val_loss: 0.0503 - val_accuracy: 0.6484
Epoch 170/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0393 - accuracy: 0.7278 - val_loss: 0.0498 - val_accuracy: 0.6504
Epoch 171/200
5625/5625 [==============================] - 18s 3ms/step - loss: 0.0392 - accuracy: 0.7276 - val_loss: 0.0494 - val_accuracy: 0.6528
Epoch 172/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0393 - accuracy: 0.7272 - val_loss: 0.0494 - val_accuracy: 0.6580
Epoch 173/200
5625/5625 [==============================] - 18s 3ms/step - loss: 0.0392 - accuracy: 0.7277 - val_loss: 0.0505 - val_accuracy: 0.6450
Epoch 174/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0392 - accuracy: 0.7277 - val_loss: 0.0495 - val_accuracy: 0.6560
Epoch 175/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0392 - accuracy: 0.7280 - val_loss: 0.0493 - val_accuracy: 0.6572
Epoch 176/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0393 - accuracy: 0.7276 - val_loss: 0.0498 - val_accuracy: 0.6540
Epoch 177/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0392 - accuracy: 0.7275 - val_loss: 0.0503 - val_accuracy: 0.6482
Epoch 178/200
5625/5625 [==============================] - 18s 3ms/step - loss: 0.0392 - accuracy: 0.7286 - val_loss: 0.0500 - val_accuracy: 0.6482
Epoch 179/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0392 - accuracy: 0.7278 - val_loss: 0.0497 - val_accuracy: 0.6520
Epoch 180/200
5625/5625 [==============================] - 18s 3ms/step - loss: 0.0392 - accuracy: 0.7279 - val_loss: 0.0499 - val_accuracy: 0.6520
Epoch 181/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0392 - accuracy: 0.7281 - val_loss: 0.0494 - val_accuracy: 0.6548
Epoch 182/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0391 - accuracy: 0.7282 - val_loss: 0.0499 - val_accuracy: 0.6514
Epoch 183/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0391 - accuracy: 0.7287 - val_loss: 0.0514 - val_accuracy: 0.6402
Epoch 184/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0392 - accuracy: 0.7291 - val_loss: 0.0505 - val_accuracy: 0.6502
Epoch 185/200
5625/5625 [==============================] - 18s 3ms/step - loss: 0.0391 - accuracy: 0.7291 - val_loss: 0.0500 - val_accuracy: 0.6502
Epoch 186/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0392 - accuracy: 0.7286 - val_loss: 0.0495 - val_accuracy: 0.6484
Epoch 187/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0392 - accuracy: 0.7287 - val_loss: 0.0496 - val_accuracy: 0.6548
Epoch 188/200
5625/5625 [==============================] - 18s 3ms/step - loss: 0.0391 - accuracy: 0.7294 - val_loss: 0.0515 - val_accuracy: 0.6386
Epoch 189/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0391 - accuracy: 0.7295 - val_loss: 0.0501 - val_accuracy: 0.6504
Epoch 190/200
5625/5625 [==============================] - 18s 3ms/step - loss: 0.0391 - accuracy: 0.7291 - val_loss: 0.0515 - val_accuracy: 0.6458
Epoch 191/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0391 - accuracy: 0.7286 - val_loss: 0.0493 - val_accuracy: 0.6548
Epoch 192/200
5625/5625 [==============================] - 18s 3ms/step - loss: 0.0392 - accuracy: 0.7282 - val_loss: 0.0495 - val_accuracy: 0.6526
Epoch 193/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0391 - accuracy: 0.7293 - val_loss: 0.0502 - val_accuracy: 0.6466
Epoch 194/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0392 - accuracy: 0.7294 - val_loss: 0.0510 - val_accuracy: 0.6480
Epoch 195/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0391 - accuracy: 0.7289 - val_loss: 0.0502 - val_accuracy: 0.6510
Epoch 196/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0391 - accuracy: 0.7285 - val_loss: 0.0503 - val_accuracy: 0.6472
Epoch 197/200
5625/5625 [==============================] - 18s 3ms/step - loss: 0.0391 - accuracy: 0.7299 - val_loss: 0.0501 - val_accuracy: 0.6468
Epoch 198/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0391 - accuracy: 0.7296 - val_loss: 0.0504 - val_accuracy: 0.6418
Epoch 199/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0392 - accuracy: 0.7295 - val_loss: 0.0502 - val_accuracy: 0.6510
Epoch 200/200
5625/5625 [==============================] - 19s 3ms/step - loss: 0.0391 - accuracy: 0.7288 - val_loss: 0.0495 - val_accuracy: 0.6532
In [ ]:
#write accuracies in a csv file
import pandas as pd
data = {'Epoch': list(range(1, len(history_aug.history['val_accuracy']) + 1)),
        'Train Accuracy' : history_aug.history['accuracy'] ,
        'Test Accuracy': history_aug.history['val_accuracy']}
df = pd.DataFrame(data)

#folder = '/content/gdrive/MyDrive/DLS-codes/HW2/csv/'
folder = '/kaggle/working/'
csv_filename = 'data-aug.csv'
df.to_csv(folder + csv_filename, index=False)
In [ ]:
#plot the test accuracies
#plot test accuracy
import matplotlib.pyplot as plt
folder = '/kaggle/working/'
csv_filename1 = 'baseline.csv'
df1 = pd.read_csv(folder + csv_filename1)
csv_filename2 = 'data-aug.csv'
df2 = pd.read_csv(folder + csv_filename2)

#plot the test accuracies from both DataFrames
plt.plot(df1['Epoch'], df1['Test Accuracy'], label='Baseline')
plt.plot(df2['Epoch'], df2['Test Accuracy'], label='Data Augmentation')
plt.xlabel('Epochs')
plt.ylabel('Validation Accuracy')
plt.legend()
plt.title('Cifar10 Baseline vs Data Augmentation')
plt.show()

Q4.

In [ ]:
from keras.datasets import cifar10
import keras
import tensorflow as tf
import numpy as np
from tensorflow.keras.layers import Conv2D, MaxPooling2D, Dense, Flatten, Dropout
from tensorflow.keras.models import Sequential
import os
import matplotlib.pyplot as plt
from keras.optimizers import Adam
In [ ]:
(x_train, y_train), (x_test, y_test) = cifar10.load_data()

Downloading data from https://www.cs.toronto.edu/~kriz/cifar-10-python.tar.gz
170498071/170498071 [==============================] - 6s 0us/step
In [ ]:
#set aside 500 examples
x_train1 = x_train[-500:]
y_train1 = y_train[-500:]

a. Pretext

In [ ]:
#assign class 0 to the 49500 images
x_train_class0 = x_train[:-500]
y_train_class0 = y_train[:-500]
In [ ]:
#check the shape of the images
x_train1.shape, y_train1.shape, x_train_class0.shape, y_train_class0.shape
Out[ ]:
((500, 32, 32, 3), (500, 1), (49500, 32, 32, 3), (49500, 1))
In [ ]:
#class 0 the 49500 x_train_unlabeled

#class 1 vertically flip upside down
x_train_class1 = x_train_class0[:,::-1,:,:]

#class 2 rotate images counterclockwise
x_train_class2 = np.rot90(x_train_class0, 1, (1,2))
In [ ]:
#print class 0 images - original
# Select 20 random indices
indices = np.random.choice(len(x_train_class0), 20)

# Plot the images
plt.figure(figsize=(10, 5))
for i, idx in enumerate(indices):
    img = x_train_class0[idx]
    plt.subplot(4, 5, i+1)
    plt.imshow(img)
    plt.axis('off')

plt.tight_layout()
plt.show()
In [ ]:
#print class 1 vertically flipped images

# Plot the images
plt.figure(figsize=(10, 5))
for i, idx in enumerate(indices):
    img = x_train_class1[idx]
    plt.subplot(4, 5, i+1)
    plt.imshow(img)
    plt.axis('off')

plt.tight_layout()
plt.show()
In [ ]:
#class 2 rotated by 90 degrees counter clock

# Plot the images
plt.figure(figsize=(10, 5))
for i, idx in enumerate(indices):
    img = x_train_class2[idx]
    plt.subplot(4, 5, i+1)
    plt.imshow(img)
    plt.axis('off')

plt.tight_layout()
plt.show()
In [ ]:
#concatenate the data
x_train_1 = np.concatenate([x_train_class0, x_train_class1, x_train_class2] , axis = 0)
y_train_1 = np.concatenate([np.zeros(len(x_train_class0)), 1*np.ones(len(x_train_class1)), 2*np.ones(len(x_train_class2))] , axis = 0)
In [ ]:
x_train_1.shape , y_train_1.shape
Out[ ]:
((148500, 32, 32, 3), (148500,))
In [ ]:
#categorical labels
#y_train_1 = keras.utils.to_categorical(y_train_1 , num_classes = 3)
In [ ]:
#normalize the x_train from 0 to 1
x_train_1 = x_train_1 / 255.0
In [ ]:
#model
model = Sequential()
model.add(Conv2D(filters = 10, kernel_size = (5, 5) , strides = (1, 1), padding = "same",input_shape = (32,32,3),
                 activation = "relu", kernel_initializer = "he_normal"))
model.add(MaxPooling2D(pool_size = (2, 2), strides = (2, 2)))
model.add(Conv2D(filters = 10, kernel_size = (5, 5) , strides = (1, 1), padding = "same",
                 activation = "relu", kernel_initializer = "he_normal"))
model.add(MaxPooling2D(pool_size = (2, 2), strides = (2, 2)))
model.add(Flatten())
model.add(Dense(20, activation = "relu", kernel_initializer = "he_normal"))
model.add(Dense(3, activation = "softmax"))
In [ ]:
model.summary()

Model: "sequential_2"
_________________________________________________________________
 Layer (type)                Output Shape              Param #   
=================================================================
 conv2d (Conv2D)             (None, 32, 32, 10)        760       
                                                                 
 max_pooling2d (MaxPooling2  (None, 16, 16, 10)        0         
 D)                                                              
                                                                 
 conv2d_1 (Conv2D)           (None, 16, 16, 10)        2510      
                                                                 
 max_pooling2d_1 (MaxPoolin  (None, 8, 8, 10)          0         
 g2D)                                                            
                                                                 
 flatten_1 (Flatten)         (None, 640)               0         
                                                                 
 dense_4 (Dense)             (None, 20)                12820     
                                                                 
 dense_5 (Dense)             (None, 3)                 63        
                                                                 
=================================================================
Total params: 16153 (63.10 KB)
Trainable params: 16153 (63.10 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
In [ ]:
#with btch size 512 : 0.7889 categorical cross entropy
#batch size 512 sparse categorical
In [ ]:
model.compile(optimizer = Adam(learning_rate = 0.001) , loss = "sparse_categorical_crossentropy" , metrics= ["accuracy"])
history_pretext = model.fit(x_train_1, y_train_1, epochs = 100 , batch_size = 512)

Epoch 1/100
291/291 [==============================] - 4s 6ms/step - loss: 0.8938 - accuracy: 0.5747
Epoch 2/100
291/291 [==============================] - 2s 6ms/step - loss: 0.7725 - accuracy: 0.6575
Epoch 3/100
291/291 [==============================] - 2s 6ms/step - loss: 0.7384 - accuracy: 0.6767
Epoch 4/100
291/291 [==============================] - 2s 6ms/step - loss: 0.7210 - accuracy: 0.6864
Epoch 5/100
291/291 [==============================] - 2s 6ms/step - loss: 0.7039 - accuracy: 0.6949
Epoch 6/100
291/291 [==============================] - 2s 6ms/step - loss: 0.6924 - accuracy: 0.7009
Epoch 7/100
291/291 [==============================] - 2s 6ms/step - loss: 0.6818 - accuracy: 0.7065
Epoch 8/100
291/291 [==============================] - 2s 6ms/step - loss: 0.6720 - accuracy: 0.7114
Epoch 9/100
291/291 [==============================] - 2s 6ms/step - loss: 0.6670 - accuracy: 0.7132
Epoch 10/100
291/291 [==============================] - 2s 6ms/step - loss: 0.6596 - accuracy: 0.7164
Epoch 11/100
291/291 [==============================] - 2s 6ms/step - loss: 0.6530 - accuracy: 0.7207
Epoch 12/100
291/291 [==============================] - 2s 6ms/step - loss: 0.6465 - accuracy: 0.7227
Epoch 13/100
291/291 [==============================] - 2s 6ms/step - loss: 0.6451 - accuracy: 0.7236
Epoch 14/100
291/291 [==============================] - 2s 6ms/step - loss: 0.6388 - accuracy: 0.7264
Epoch 15/100
291/291 [==============================] - 2s 6ms/step - loss: 0.6328 - accuracy: 0.7303
Epoch 16/100
291/291 [==============================] - 2s 6ms/step - loss: 0.6289 - accuracy: 0.7316
Epoch 17/100
291/291 [==============================] - 2s 6ms/step - loss: 0.6260 - accuracy: 0.7331
Epoch 18/100
291/291 [==============================] - 2s 6ms/step - loss: 0.6227 - accuracy: 0.7337
Epoch 19/100
291/291 [==============================] - 2s 6ms/step - loss: 0.6166 - accuracy: 0.7369
Epoch 20/100
291/291 [==============================] - 2s 6ms/step - loss: 0.6161 - accuracy: 0.7381
Epoch 21/100
291/291 [==============================] - 2s 6ms/step - loss: 0.6107 - accuracy: 0.7397
Epoch 22/100
291/291 [==============================] - 2s 6ms/step - loss: 0.6096 - accuracy: 0.7409
Epoch 23/100
291/291 [==============================] - 2s 6ms/step - loss: 0.6056 - accuracy: 0.7427
Epoch 24/100
291/291 [==============================] - 2s 6ms/step - loss: 0.6035 - accuracy: 0.7436
Epoch 25/100
291/291 [==============================] - 2s 6ms/step - loss: 0.6018 - accuracy: 0.7438
Epoch 26/100
291/291 [==============================] - 2s 6ms/step - loss: 0.5977 - accuracy: 0.7458
Epoch 27/100
291/291 [==============================] - 2s 6ms/step - loss: 0.5965 - accuracy: 0.7475
Epoch 28/100
291/291 [==============================] - 2s 6ms/step - loss: 0.5929 - accuracy: 0.7492
Epoch 29/100
291/291 [==============================] - 2s 6ms/step - loss: 0.5934 - accuracy: 0.7481
Epoch 30/100
291/291 [==============================] - 2s 6ms/step - loss: 0.5898 - accuracy: 0.7514
Epoch 31/100
291/291 [==============================] - 2s 6ms/step - loss: 0.5886 - accuracy: 0.7514
Epoch 32/100
291/291 [==============================] - 2s 6ms/step - loss: 0.5849 - accuracy: 0.7529
Epoch 33/100
291/291 [==============================] - 2s 6ms/step - loss: 0.5861 - accuracy: 0.7519
Epoch 34/100
291/291 [==============================] - 2s 6ms/step - loss: 0.5819 - accuracy: 0.7545
Epoch 35/100
291/291 [==============================] - 2s 6ms/step - loss: 0.5801 - accuracy: 0.7553
Epoch 36/100
291/291 [==============================] - 2s 6ms/step - loss: 0.5780 - accuracy: 0.7569
Epoch 37/100
291/291 [==============================] - 2s 6ms/step - loss: 0.5758 - accuracy: 0.7580
Epoch 38/100
291/291 [==============================] - 2s 6ms/step - loss: 0.5777 - accuracy: 0.7566
Epoch 39/100
291/291 [==============================] - 2s 6ms/step - loss: 0.5715 - accuracy: 0.7594
Epoch 40/100
291/291 [==============================] - 2s 6ms/step - loss: 0.5725 - accuracy: 0.7591
Epoch 41/100
291/291 [==============================] - 2s 6ms/step - loss: 0.5703 - accuracy: 0.7603
Epoch 42/100
291/291 [==============================] - 2s 6ms/step - loss: 0.5689 - accuracy: 0.7618
Epoch 43/100
291/291 [==============================] - 2s 6ms/step - loss: 0.5686 - accuracy: 0.7620
Epoch 44/100
291/291 [==============================] - 2s 6ms/step - loss: 0.5661 - accuracy: 0.7629
Epoch 45/100
291/291 [==============================] - 2s 6ms/step - loss: 0.5633 - accuracy: 0.7639
Epoch 46/100
291/291 [==============================] - 2s 6ms/step - loss: 0.5629 - accuracy: 0.7641
Epoch 47/100
291/291 [==============================] - 2s 6ms/step - loss: 0.5637 - accuracy: 0.7639
Epoch 48/100
291/291 [==============================] - 2s 6ms/step - loss: 0.5614 - accuracy: 0.7642
Epoch 49/100
291/291 [==============================] - 2s 6ms/step - loss: 0.5577 - accuracy: 0.7668
Epoch 50/100
291/291 [==============================] - 2s 6ms/step - loss: 0.5584 - accuracy: 0.7664
Epoch 51/100
291/291 [==============================] - 2s 6ms/step - loss: 0.5572 - accuracy: 0.7668
Epoch 52/100
291/291 [==============================] - 2s 6ms/step - loss: 0.5577 - accuracy: 0.7666
Epoch 53/100
291/291 [==============================] - 2s 6ms/step - loss: 0.5554 - accuracy: 0.7677
Epoch 54/100
291/291 [==============================] - 2s 6ms/step - loss: 0.5551 - accuracy: 0.7675
Epoch 55/100
291/291 [==============================] - 2s 6ms/step - loss: 0.5541 - accuracy: 0.7686
Epoch 56/100
291/291 [==============================] - 2s 6ms/step - loss: 0.5516 - accuracy: 0.7697
Epoch 57/100
291/291 [==============================] - 2s 6ms/step - loss: 0.5506 - accuracy: 0.7696
Epoch 58/100
291/291 [==============================] - 2s 6ms/step - loss: 0.5500 - accuracy: 0.7705
Epoch 59/100
291/291 [==============================] - 2s 6ms/step - loss: 0.5500 - accuracy: 0.7702
Epoch 60/100
291/291 [==============================] - 2s 6ms/step - loss: 0.5496 - accuracy: 0.7695
Epoch 61/100
291/291 [==============================] - 2s 6ms/step - loss: 0.5473 - accuracy: 0.7719
Epoch 62/100
291/291 [==============================] - 2s 6ms/step - loss: 0.5465 - accuracy: 0.7717
Epoch 63/100
291/291 [==============================] - 2s 6ms/step - loss: 0.5444 - accuracy: 0.7722
Epoch 64/100
291/291 [==============================] - 2s 6ms/step - loss: 0.5461 - accuracy: 0.7713
Epoch 65/100
291/291 [==============================] - 2s 6ms/step - loss: 0.5471 - accuracy: 0.7712
Epoch 66/100
291/291 [==============================] - 2s 6ms/step - loss: 0.5423 - accuracy: 0.7738
Epoch 67/100
291/291 [==============================] - 2s 6ms/step - loss: 0.5449 - accuracy: 0.7728
Epoch 68/100
291/291 [==============================] - 2s 6ms/step - loss: 0.5418 - accuracy: 0.7742
Epoch 69/100
291/291 [==============================] - 2s 6ms/step - loss: 0.5414 - accuracy: 0.7742
Epoch 70/100
291/291 [==============================] - 2s 6ms/step - loss: 0.5419 - accuracy: 0.7741
Epoch 71/100
291/291 [==============================] - 2s 6ms/step - loss: 0.5381 - accuracy: 0.7762
Epoch 72/100
291/291 [==============================] - 2s 6ms/step - loss: 0.5375 - accuracy: 0.7762
Epoch 73/100
291/291 [==============================] - 2s 6ms/step - loss: 0.5387 - accuracy: 0.7758
Epoch 74/100
291/291 [==============================] - 2s 6ms/step - loss: 0.5380 - accuracy: 0.7755
Epoch 75/100
291/291 [==============================] - 2s 6ms/step - loss: 0.5398 - accuracy: 0.7741
Epoch 76/100
291/291 [==============================] - 2s 6ms/step - loss: 0.5375 - accuracy: 0.7764
Epoch 77/100
291/291 [==============================] - 2s 6ms/step - loss: 0.5365 - accuracy: 0.7769
Epoch 78/100
291/291 [==============================] - 2s 6ms/step - loss: 0.5355 - accuracy: 0.7764
Epoch 79/100
291/291 [==============================] - 2s 6ms/step - loss: 0.5340 - accuracy: 0.7782
Epoch 80/100
291/291 [==============================] - 2s 6ms/step - loss: 0.5329 - accuracy: 0.7780
Epoch 81/100
291/291 [==============================] - 2s 6ms/step - loss: 0.5339 - accuracy: 0.7781
Epoch 82/100
291/291 [==============================] - 2s 6ms/step - loss: 0.5338 - accuracy: 0.7776
Epoch 83/100
291/291 [==============================] - 2s 6ms/step - loss: 0.5333 - accuracy: 0.7772
Epoch 84/100
291/291 [==============================] - 2s 6ms/step - loss: 0.5322 - accuracy: 0.7784
Epoch 85/100
291/291 [==============================] - 2s 6ms/step - loss: 0.5302 - accuracy: 0.7803
Epoch 86/100
291/291 [==============================] - 2s 6ms/step - loss: 0.5315 - accuracy: 0.7796
Epoch 87/100
291/291 [==============================] - 2s 6ms/step - loss: 0.5313 - accuracy: 0.7799
Epoch 88/100
291/291 [==============================] - 2s 6ms/step - loss: 0.5298 - accuracy: 0.7796
Epoch 89/100
291/291 [==============================] - 2s 6ms/step - loss: 0.5288 - accuracy: 0.7794
Epoch 90/100
291/291 [==============================] - 2s 6ms/step - loss: 0.5285 - accuracy: 0.7808
Epoch 91/100
291/291 [==============================] - 2s 6ms/step - loss: 0.5265 - accuracy: 0.7814
Epoch 92/100
291/291 [==============================] - 2s 6ms/step - loss: 0.5261 - accuracy: 0.7813
Epoch 93/100
291/291 [==============================] - 2s 6ms/step - loss: 0.5256 - accuracy: 0.7820
Epoch 94/100
291/291 [==============================] - 2s 6ms/step - loss: 0.5237 - accuracy: 0.7825
Epoch 95/100
291/291 [==============================] - 2s 6ms/step - loss: 0.5263 - accuracy: 0.7815
Epoch 96/100
291/291 [==============================] - 2s 6ms/step - loss: 0.5251 - accuracy: 0.7823
Epoch 97/100
291/291 [==============================] - 2s 6ms/step - loss: 0.5242 - accuracy: 0.7822
Epoch 98/100
291/291 [==============================] - 2s 6ms/step - loss: 0.5230 - accuracy: 0.7833
Epoch 99/100
291/291 [==============================] - 2s 6ms/step - loss: 0.5242 - accuracy: 0.7828
Epoch 100/100
291/291 [==============================] - 2s 6ms/step - loss: 0.5260 - accuracy: 0.7812
In [ ]:
model.save("/content/gdrive/MyDrive/DLS/HW2/pretext.h5")

b. Baseline

In [ ]:
x_train1.shape , y_train1.shape
Out[ ]:
((500, 32, 32, 3), (500, 1))
In [ ]:
#normalize x train
x_train1 = x_train1 / 255.0
In [ ]:
#normalize validation data
x_val = x_test / 255.0
In [ ]:
#categorical labels
#y_train1 = keras.utils.to_categorical(y_train1, num_classes = 10)
#y_val = keras.utils.to_categorical(y_test, num_classes = 10)
y_val = y_test
In [ ]:
#model
model = Sequential()
model.add(Conv2D(filters = 10, kernel_size = (5, 5) , strides = (1, 1), padding = "same",input_shape = (32,32,3),
                 activation = "relu", kernel_initializer = "he_normal"))
model.add(MaxPooling2D(pool_size = (2, 2), strides = (2, 2)))
model.add(Conv2D(filters = 10, kernel_size = (5, 5) , strides = (1, 1), padding = "same",
                 activation = "relu", kernel_initializer = "he_normal"))
model.add(MaxPooling2D(pool_size = (2, 2), strides = (2, 2)))
model.add(Flatten())
model.add(Dense(20, activation = "relu" , kernel_initializer = "he_normal"))
model.add(Dense(10, activation = "softmax"))
In [ ]:
model.summary()

Model: "sequential_3"
_________________________________________________________________
 Layer (type)                Output Shape              Param #   
=================================================================
 conv2d_2 (Conv2D)           (None, 32, 32, 10)        760       
                                                                 
 max_pooling2d_2 (MaxPoolin  (None, 16, 16, 10)        0         
 g2D)                                                            
                                                                 
 conv2d_3 (Conv2D)           (None, 16, 16, 10)        2510      
                                                                 
 max_pooling2d_3 (MaxPoolin  (None, 8, 8, 10)          0         
 g2D)                                                            
                                                                 
 flatten_2 (Flatten)         (None, 640)               0         
                                                                 
 dense_6 (Dense)             (None, 20)                12820     
                                                                 
 dense_7 (Dense)             (None, 10)                210       
                                                                 
=================================================================
Total params: 16300 (63.67 KB)
Trainable params: 16300 (63.67 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
In [ ]:
model.compile(optimizer = Adam(learning_rate = 0.001) , loss = "sparse_categorical_crossentropy" , metrics= ["accuracy"])
history_baseline = model.fit(x_train1, y_train1, epochs = 10000 , batch_size = 500, validation_data = (x_val, y_val))

Streaming output truncated to the last 5000 lines.
1/1 [==============================] - 0s 103ms/step - loss: 6.3416e-06 - accuracy: 1.0000 - val_loss: 13.6898 - val_accuracy: 0.3161
Epoch 7502/10000
1/1 [==============================] - 0s 108ms/step - loss: 6.3357e-06 - accuracy: 1.0000 - val_loss: 13.6909 - val_accuracy: 0.3162
Epoch 7503/10000
1/1 [==============================] - 0s 111ms/step - loss: 6.3288e-06 - accuracy: 1.0000 - val_loss: 13.6917 - val_accuracy: 0.3160
Epoch 7504/10000
1/1 [==============================] - 0s 109ms/step - loss: 6.3273e-06 - accuracy: 1.0000 - val_loss: 13.6919 - val_accuracy: 0.3159
Epoch 7505/10000
1/1 [==============================] - 0s 105ms/step - loss: 6.3252e-06 - accuracy: 1.0000 - val_loss: 13.6920 - val_accuracy: 0.3161
Epoch 7506/10000
1/1 [==============================] - 0s 101ms/step - loss: 6.3221e-06 - accuracy: 1.0000 - val_loss: 13.6923 - val_accuracy: 0.3162
Epoch 7507/10000
1/1 [==============================] - 0s 105ms/step - loss: 6.3207e-06 - accuracy: 1.0000 - val_loss: 13.6932 - val_accuracy: 0.3162
Epoch 7508/10000
1/1 [==============================] - 0s 106ms/step - loss: 6.3135e-06 - accuracy: 1.0000 - val_loss: 13.6944 - val_accuracy: 0.3160
Epoch 7509/10000
1/1 [==============================] - 0s 106ms/step - loss: 6.3111e-06 - accuracy: 1.0000 - val_loss: 13.6948 - val_accuracy: 0.3159
Epoch 7510/10000
1/1 [==============================] - 0s 107ms/step - loss: 6.3040e-06 - accuracy: 1.0000 - val_loss: 13.6947 - val_accuracy: 0.3160
Epoch 7511/10000
1/1 [==============================] - 0s 107ms/step - loss: 6.2999e-06 - accuracy: 1.0000 - val_loss: 13.6955 - val_accuracy: 0.3162
Epoch 7512/10000
1/1 [==============================] - 0s 106ms/step - loss: 6.2975e-06 - accuracy: 1.0000 - val_loss: 13.6971 - val_accuracy: 0.3162
Epoch 7513/10000
1/1 [==============================] - 0s 107ms/step - loss: 6.2937e-06 - accuracy: 1.0000 - val_loss: 13.6979 - val_accuracy: 0.3160
Epoch 7514/10000
1/1 [==============================] - 0s 101ms/step - loss: 6.2918e-06 - accuracy: 1.0000 - val_loss: 13.6979 - val_accuracy: 0.3159
Epoch 7515/10000
1/1 [==============================] - 0s 106ms/step - loss: 6.2885e-06 - accuracy: 1.0000 - val_loss: 13.6973 - val_accuracy: 0.3160
Epoch 7516/10000
1/1 [==============================] - 0s 101ms/step - loss: 6.2832e-06 - accuracy: 1.0000 - val_loss: 13.6977 - val_accuracy: 0.3161
Epoch 7517/10000
1/1 [==============================] - 0s 103ms/step - loss: 6.2792e-06 - accuracy: 1.0000 - val_loss: 13.6994 - val_accuracy: 0.3162
Epoch 7518/10000
1/1 [==============================] - 0s 101ms/step - loss: 6.2727e-06 - accuracy: 1.0000 - val_loss: 13.7017 - val_accuracy: 0.3162
Epoch 7519/10000
1/1 [==============================] - 0s 102ms/step - loss: 6.2727e-06 - accuracy: 1.0000 - val_loss: 13.7020 - val_accuracy: 0.3160
Epoch 7520/10000
1/1 [==============================] - 0s 101ms/step - loss: 6.2696e-06 - accuracy: 1.0000 - val_loss: 13.7014 - val_accuracy: 0.3159
Epoch 7521/10000
1/1 [==============================] - 0s 100ms/step - loss: 6.2627e-06 - accuracy: 1.0000 - val_loss: 13.7007 - val_accuracy: 0.3159
Epoch 7522/10000
1/1 [==============================] - 0s 99ms/step - loss: 6.2589e-06 - accuracy: 1.0000 - val_loss: 13.7013 - val_accuracy: 0.3160
Epoch 7523/10000
1/1 [==============================] - 0s 107ms/step - loss: 6.2560e-06 - accuracy: 1.0000 - val_loss: 13.7030 - val_accuracy: 0.3160
Epoch 7524/10000
1/1 [==============================] - 0s 105ms/step - loss: 6.2515e-06 - accuracy: 1.0000 - val_loss: 13.7051 - val_accuracy: 0.3160
Epoch 7525/10000
1/1 [==============================] - 0s 110ms/step - loss: 6.2479e-06 - accuracy: 1.0000 - val_loss: 13.7056 - val_accuracy: 0.3161
Epoch 7526/10000
1/1 [==============================] - 0s 100ms/step - loss: 6.2496e-06 - accuracy: 1.0000 - val_loss: 13.7045 - val_accuracy: 0.3162
Epoch 7527/10000
1/1 [==============================] - 0s 101ms/step - loss: 6.2425e-06 - accuracy: 1.0000 - val_loss: 13.7042 - val_accuracy: 0.3159
Epoch 7528/10000
1/1 [==============================] - 0s 102ms/step - loss: 6.2384e-06 - accuracy: 1.0000 - val_loss: 13.7048 - val_accuracy: 0.3158
Epoch 7529/10000
1/1 [==============================] - 0s 108ms/step - loss: 6.2365e-06 - accuracy: 1.0000 - val_loss: 13.7060 - val_accuracy: 0.3158
Epoch 7530/10000
1/1 [==============================] - 0s 109ms/step - loss: 6.2322e-06 - accuracy: 1.0000 - val_loss: 13.7066 - val_accuracy: 0.3161
Epoch 7531/10000
1/1 [==============================] - 0s 103ms/step - loss: 6.2258e-06 - accuracy: 1.0000 - val_loss: 13.7076 - val_accuracy: 0.3162
Epoch 7532/10000
1/1 [==============================] - 0s 104ms/step - loss: 6.2229e-06 - accuracy: 1.0000 - val_loss: 13.7090 - val_accuracy: 0.3159
Epoch 7533/10000
1/1 [==============================] - 0s 104ms/step - loss: 6.2196e-06 - accuracy: 1.0000 - val_loss: 13.7101 - val_accuracy: 0.3158
Epoch 7534/10000
1/1 [==============================] - 0s 104ms/step - loss: 6.2158e-06 - accuracy: 1.0000 - val_loss: 13.7103 - val_accuracy: 0.3159
Epoch 7535/10000
1/1 [==============================] - 0s 104ms/step - loss: 6.2127e-06 - accuracy: 1.0000 - val_loss: 13.7102 - val_accuracy: 0.3161
Epoch 7536/10000
1/1 [==============================] - 0s 101ms/step - loss: 6.2069e-06 - accuracy: 1.0000 - val_loss: 13.7103 - val_accuracy: 0.3162
Epoch 7537/10000
1/1 [==============================] - 0s 110ms/step - loss: 6.2036e-06 - accuracy: 1.0000 - val_loss: 13.7112 - val_accuracy: 0.3160
Epoch 7538/10000
1/1 [==============================] - 0s 107ms/step - loss: 6.1967e-06 - accuracy: 1.0000 - val_loss: 13.7126 - val_accuracy: 0.3159
Epoch 7539/10000
1/1 [==============================] - 0s 106ms/step - loss: 6.1969e-06 - accuracy: 1.0000 - val_loss: 13.7133 - val_accuracy: 0.3159
Epoch 7540/10000
1/1 [==============================] - 0s 107ms/step - loss: 6.1936e-06 - accuracy: 1.0000 - val_loss: 13.7137 - val_accuracy: 0.3160
Epoch 7541/10000
1/1 [==============================] - 0s 106ms/step - loss: 6.1898e-06 - accuracy: 1.0000 - val_loss: 13.7137 - val_accuracy: 0.3160
Epoch 7542/10000
1/1 [==============================] - 0s 101ms/step - loss: 6.1838e-06 - accuracy: 1.0000 - val_loss: 13.7145 - val_accuracy: 0.3160
Epoch 7543/10000
1/1 [==============================] - 0s 104ms/step - loss: 6.1793e-06 - accuracy: 1.0000 - val_loss: 13.7152 - val_accuracy: 0.3159
Epoch 7544/10000
1/1 [==============================] - 0s 105ms/step - loss: 6.1767e-06 - accuracy: 1.0000 - val_loss: 13.7156 - val_accuracy: 0.3160
Epoch 7545/10000
1/1 [==============================] - 0s 112ms/step - loss: 6.1709e-06 - accuracy: 1.0000 - val_loss: 13.7162 - val_accuracy: 0.3161
Epoch 7546/10000
1/1 [==============================] - 0s 104ms/step - loss: 6.1681e-06 - accuracy: 1.0000 - val_loss: 13.7175 - val_accuracy: 0.3160
Epoch 7547/10000
1/1 [==============================] - 0s 112ms/step - loss: 6.1638e-06 - accuracy: 1.0000 - val_loss: 13.7182 - val_accuracy: 0.3159
Epoch 7548/10000
1/1 [==============================] - 0s 107ms/step - loss: 6.1614e-06 - accuracy: 1.0000 - val_loss: 13.7178 - val_accuracy: 0.3160
Epoch 7549/10000
1/1 [==============================] - 0s 111ms/step - loss: 6.1557e-06 - accuracy: 1.0000 - val_loss: 13.7182 - val_accuracy: 0.3160
Epoch 7550/10000
1/1 [==============================] - 0s 112ms/step - loss: 6.1511e-06 - accuracy: 1.0000 - val_loss: 13.7195 - val_accuracy: 0.3160
Epoch 7551/10000
1/1 [==============================] - 0s 114ms/step - loss: 6.1488e-06 - accuracy: 1.0000 - val_loss: 13.7208 - val_accuracy: 0.3160
Epoch 7552/10000
1/1 [==============================] - 0s 108ms/step - loss: 6.1423e-06 - accuracy: 1.0000 - val_loss: 13.7211 - val_accuracy: 0.3160
Epoch 7553/10000
1/1 [==============================] - 0s 105ms/step - loss: 6.1397e-06 - accuracy: 1.0000 - val_loss: 13.7208 - val_accuracy: 0.3159
Epoch 7554/10000
1/1 [==============================] - 0s 107ms/step - loss: 6.1359e-06 - accuracy: 1.0000 - val_loss: 13.7212 - val_accuracy: 0.3160
Epoch 7555/10000
1/1 [==============================] - 0s 102ms/step - loss: 6.1316e-06 - accuracy: 1.0000 - val_loss: 13.7219 - val_accuracy: 0.3159
Epoch 7556/10000
1/1 [==============================] - 0s 106ms/step - loss: 6.1278e-06 - accuracy: 1.0000 - val_loss: 13.7232 - val_accuracy: 0.3161
Epoch 7557/10000
1/1 [==============================] - 0s 113ms/step - loss: 6.1242e-06 - accuracy: 1.0000 - val_loss: 13.7244 - val_accuracy: 0.3159
Epoch 7558/10000
1/1 [==============================] - 0s 102ms/step - loss: 6.1223e-06 - accuracy: 1.0000 - val_loss: 13.7243 - val_accuracy: 0.3159
Epoch 7559/10000
1/1 [==============================] - 0s 116ms/step - loss: 6.1168e-06 - accuracy: 1.0000 - val_loss: 13.7242 - val_accuracy: 0.3159
Epoch 7560/10000
1/1 [==============================] - 0s 100ms/step - loss: 6.1125e-06 - accuracy: 1.0000 - val_loss: 13.7243 - val_accuracy: 0.3160
Epoch 7561/10000
1/1 [==============================] - 0s 102ms/step - loss: 6.1070e-06 - accuracy: 1.0000 - val_loss: 13.7253 - val_accuracy: 0.3159
Epoch 7562/10000
1/1 [==============================] - 0s 101ms/step - loss: 6.1042e-06 - accuracy: 1.0000 - val_loss: 13.7264 - val_accuracy: 0.3159
Epoch 7563/10000
1/1 [==============================] - 0s 106ms/step - loss: 6.1013e-06 - accuracy: 1.0000 - val_loss: 13.7277 - val_accuracy: 0.3158
Epoch 7564/10000
1/1 [==============================] - 0s 100ms/step - loss: 6.1006e-06 - accuracy: 1.0000 - val_loss: 13.7282 - val_accuracy: 0.3159
Epoch 7565/10000
1/1 [==============================] - 0s 103ms/step - loss: 6.0956e-06 - accuracy: 1.0000 - val_loss: 13.7283 - val_accuracy: 0.3160
Epoch 7566/10000
1/1 [==============================] - 0s 109ms/step - loss: 6.0954e-06 - accuracy: 1.0000 - val_loss: 13.7282 - val_accuracy: 0.3159
Epoch 7567/10000
1/1 [==============================] - 0s 104ms/step - loss: 6.0925e-06 - accuracy: 1.0000 - val_loss: 13.7289 - val_accuracy: 0.3159
Epoch 7568/10000
1/1 [==============================] - 0s 102ms/step - loss: 6.0851e-06 - accuracy: 1.0000 - val_loss: 13.7302 - val_accuracy: 0.3159
Epoch 7569/10000
1/1 [==============================] - 0s 101ms/step - loss: 6.0799e-06 - accuracy: 1.0000 - val_loss: 13.7311 - val_accuracy: 0.3159
Epoch 7570/10000
1/1 [==============================] - 0s 107ms/step - loss: 6.0758e-06 - accuracy: 1.0000 - val_loss: 13.7316 - val_accuracy: 0.3159
Epoch 7571/10000
1/1 [==============================] - 0s 108ms/step - loss: 6.0744e-06 - accuracy: 1.0000 - val_loss: 13.7320 - val_accuracy: 0.3160
Epoch 7572/10000
1/1 [==============================] - 0s 102ms/step - loss: 6.0694e-06 - accuracy: 1.0000 - val_loss: 13.7324 - val_accuracy: 0.3159
Epoch 7573/10000
1/1 [==============================] - 0s 103ms/step - loss: 6.0701e-06 - accuracy: 1.0000 - val_loss: 13.7330 - val_accuracy: 0.3160
Epoch 7574/10000
1/1 [==============================] - 0s 101ms/step - loss: 6.0658e-06 - accuracy: 1.0000 - val_loss: 13.7340 - val_accuracy: 0.3160
Epoch 7575/10000
1/1 [==============================] - 0s 107ms/step - loss: 6.0610e-06 - accuracy: 1.0000 - val_loss: 13.7347 - val_accuracy: 0.3159
Epoch 7576/10000
1/1 [==============================] - 0s 101ms/step - loss: 6.0570e-06 - accuracy: 1.0000 - val_loss: 13.7350 - val_accuracy: 0.3159
Epoch 7577/10000
1/1 [==============================] - 0s 102ms/step - loss: 6.0496e-06 - accuracy: 1.0000 - val_loss: 13.7352 - val_accuracy: 0.3159
Epoch 7578/10000
1/1 [==============================] - 0s 105ms/step - loss: 6.0472e-06 - accuracy: 1.0000 - val_loss: 13.7360 - val_accuracy: 0.3159
Epoch 7579/10000
1/1 [==============================] - 0s 103ms/step - loss: 6.0453e-06 - accuracy: 1.0000 - val_loss: 13.7373 - val_accuracy: 0.3160
Epoch 7580/10000
1/1 [==============================] - 0s 105ms/step - loss: 6.0412e-06 - accuracy: 1.0000 - val_loss: 13.7377 - val_accuracy: 0.3159
Epoch 7581/10000
1/1 [==============================] - 0s 107ms/step - loss: 6.0381e-06 - accuracy: 1.0000 - val_loss: 13.7379 - val_accuracy: 0.3159
Epoch 7582/10000
1/1 [==============================] - 0s 107ms/step - loss: 6.0343e-06 - accuracy: 1.0000 - val_loss: 13.7384 - val_accuracy: 0.3159
Epoch 7583/10000
1/1 [==============================] - 0s 105ms/step - loss: 6.0305e-06 - accuracy: 1.0000 - val_loss: 13.7391 - val_accuracy: 0.3159
Epoch 7584/10000
1/1 [==============================] - 0s 101ms/step - loss: 6.0262e-06 - accuracy: 1.0000 - val_loss: 13.7397 - val_accuracy: 0.3159
Epoch 7585/10000
1/1 [==============================] - 0s 105ms/step - loss: 6.0248e-06 - accuracy: 1.0000 - val_loss: 13.7408 - val_accuracy: 0.3159
Epoch 7586/10000
1/1 [==============================] - 0s 103ms/step - loss: 6.0207e-06 - accuracy: 1.0000 - val_loss: 13.7410 - val_accuracy: 0.3159
Epoch 7587/10000
1/1 [==============================] - 0s 105ms/step - loss: 6.0188e-06 - accuracy: 1.0000 - val_loss: 13.7409 - val_accuracy: 0.3159
Epoch 7588/10000
1/1 [==============================] - 0s 106ms/step - loss: 6.0112e-06 - accuracy: 1.0000 - val_loss: 13.7414 - val_accuracy: 0.3159
Epoch 7589/10000
1/1 [==============================] - 0s 105ms/step - loss: 6.0112e-06 - accuracy: 1.0000 - val_loss: 13.7427 - val_accuracy: 0.3159
Epoch 7590/10000
1/1 [==============================] - 0s 103ms/step - loss: 6.0038e-06 - accuracy: 1.0000 - val_loss: 13.7441 - val_accuracy: 0.3158
Epoch 7591/10000
1/1 [==============================] - 0s 102ms/step - loss: 6.0043e-06 - accuracy: 1.0000 - val_loss: 13.7439 - val_accuracy: 0.3159
Epoch 7592/10000
1/1 [==============================] - 0s 101ms/step - loss: 5.9990e-06 - accuracy: 1.0000 - val_loss: 13.7439 - val_accuracy: 0.3158
Epoch 7593/10000
1/1 [==============================] - 0s 103ms/step - loss: 5.9967e-06 - accuracy: 1.0000 - val_loss: 13.7445 - val_accuracy: 0.3159
Epoch 7594/10000
1/1 [==============================] - 0s 101ms/step - loss: 5.9924e-06 - accuracy: 1.0000 - val_loss: 13.7452 - val_accuracy: 0.3159
Epoch 7595/10000
1/1 [==============================] - 0s 107ms/step - loss: 5.9890e-06 - accuracy: 1.0000 - val_loss: 13.7462 - val_accuracy: 0.3159
Epoch 7596/10000
1/1 [==============================] - 0s 106ms/step - loss: 5.9852e-06 - accuracy: 1.0000 - val_loss: 13.7470 - val_accuracy: 0.3159
Epoch 7597/10000
1/1 [==============================] - 0s 104ms/step - loss: 5.9795e-06 - accuracy: 1.0000 - val_loss: 13.7479 - val_accuracy: 0.3158
Epoch 7598/10000
1/1 [==============================] - 0s 105ms/step - loss: 5.9778e-06 - accuracy: 1.0000 - val_loss: 13.7486 - val_accuracy: 0.3158
Epoch 7599/10000
1/1 [==============================] - 0s 107ms/step - loss: 5.9711e-06 - accuracy: 1.0000 - val_loss: 13.7485 - val_accuracy: 0.3159
Epoch 7600/10000
1/1 [==============================] - 0s 106ms/step - loss: 5.9671e-06 - accuracy: 1.0000 - val_loss: 13.7491 - val_accuracy: 0.3160
Epoch 7601/10000
1/1 [==============================] - 0s 103ms/step - loss: 5.9671e-06 - accuracy: 1.0000 - val_loss: 13.7502 - val_accuracy: 0.3158
Epoch 7602/10000
1/1 [==============================] - 0s 112ms/step - loss: 5.9618e-06 - accuracy: 1.0000 - val_loss: 13.7505 - val_accuracy: 0.3159
Epoch 7603/10000
1/1 [==============================] - 0s 107ms/step - loss: 5.9592e-06 - accuracy: 1.0000 - val_loss: 13.7507 - val_accuracy: 0.3159
Epoch 7604/10000
1/1 [==============================] - 0s 108ms/step - loss: 5.9576e-06 - accuracy: 1.0000 - val_loss: 13.7511 - val_accuracy: 0.3159
Epoch 7605/10000
1/1 [==============================] - 0s 106ms/step - loss: 5.9549e-06 - accuracy: 1.0000 - val_loss: 13.7523 - val_accuracy: 0.3159
Epoch 7606/10000
1/1 [==============================] - 0s 107ms/step - loss: 5.9480e-06 - accuracy: 1.0000 - val_loss: 13.7536 - val_accuracy: 0.3158
Epoch 7607/10000
1/1 [==============================] - 0s 107ms/step - loss: 5.9442e-06 - accuracy: 1.0000 - val_loss: 13.7535 - val_accuracy: 0.3159
Epoch 7608/10000
1/1 [==============================] - 0s 110ms/step - loss: 5.9411e-06 - accuracy: 1.0000 - val_loss: 13.7535 - val_accuracy: 0.3159
Epoch 7609/10000
1/1 [==============================] - 0s 103ms/step - loss: 5.9359e-06 - accuracy: 1.0000 - val_loss: 13.7547 - val_accuracy: 0.3160
Epoch 7610/10000
1/1 [==============================] - 0s 108ms/step - loss: 5.9335e-06 - accuracy: 1.0000 - val_loss: 13.7562 - val_accuracy: 0.3158
Epoch 7611/10000
1/1 [==============================] - 0s 103ms/step - loss: 5.9306e-06 - accuracy: 1.0000 - val_loss: 13.7560 - val_accuracy: 0.3159
Epoch 7612/10000
1/1 [==============================] - 0s 105ms/step - loss: 5.9249e-06 - accuracy: 1.0000 - val_loss: 13.7555 - val_accuracy: 0.3159
Epoch 7613/10000
1/1 [==============================] - 0s 103ms/step - loss: 5.9225e-06 - accuracy: 1.0000 - val_loss: 13.7563 - val_accuracy: 0.3159
Epoch 7614/10000
1/1 [==============================] - 0s 105ms/step - loss: 5.9175e-06 - accuracy: 1.0000 - val_loss: 13.7581 - val_accuracy: 0.3159
Epoch 7615/10000
1/1 [==============================] - 0s 102ms/step - loss: 5.9144e-06 - accuracy: 1.0000 - val_loss: 13.7587 - val_accuracy: 0.3159
Epoch 7616/10000
1/1 [==============================] - 0s 99ms/step - loss: 5.9108e-06 - accuracy: 1.0000 - val_loss: 13.7586 - val_accuracy: 0.3159
Epoch 7617/10000
1/1 [==============================] - 0s 103ms/step - loss: 5.9096e-06 - accuracy: 1.0000 - val_loss: 13.7590 - val_accuracy: 0.3160
Epoch 7618/10000
1/1 [==============================] - 0s 105ms/step - loss: 5.9070e-06 - accuracy: 1.0000 - val_loss: 13.7601 - val_accuracy: 0.3160
Epoch 7619/10000
1/1 [==============================] - 0s 105ms/step - loss: 5.9008e-06 - accuracy: 1.0000 - val_loss: 13.7608 - val_accuracy: 0.3158
Epoch 7620/10000
1/1 [==============================] - 0s 101ms/step - loss: 5.8979e-06 - accuracy: 1.0000 - val_loss: 13.7614 - val_accuracy: 0.3160
Epoch 7621/10000
1/1 [==============================] - 0s 107ms/step - loss: 5.8968e-06 - accuracy: 1.0000 - val_loss: 13.7620 - val_accuracy: 0.3160
Epoch 7622/10000
1/1 [==============================] - 0s 102ms/step - loss: 5.8929e-06 - accuracy: 1.0000 - val_loss: 13.7627 - val_accuracy: 0.3159
Epoch 7623/10000
1/1 [==============================] - 0s 106ms/step - loss: 5.8872e-06 - accuracy: 1.0000 - val_loss: 13.7632 - val_accuracy: 0.3158
Epoch 7624/10000
1/1 [==============================] - 0s 105ms/step - loss: 5.8836e-06 - accuracy: 1.0000 - val_loss: 13.7631 - val_accuracy: 0.3158
Epoch 7625/10000
1/1 [==============================] - 0s 107ms/step - loss: 5.8774e-06 - accuracy: 1.0000 - val_loss: 13.7636 - val_accuracy: 0.3159
Epoch 7626/10000
1/1 [==============================] - 0s 104ms/step - loss: 5.8741e-06 - accuracy: 1.0000 - val_loss: 13.7648 - val_accuracy: 0.3159
Epoch 7627/10000
1/1 [==============================] - 0s 102ms/step - loss: 5.8724e-06 - accuracy: 1.0000 - val_loss: 13.7661 - val_accuracy: 0.3159
Epoch 7628/10000
1/1 [==============================] - 0s 106ms/step - loss: 5.8722e-06 - accuracy: 1.0000 - val_loss: 13.7670 - val_accuracy: 0.3158
Epoch 7629/10000
1/1 [==============================] - 0s 103ms/step - loss: 5.8684e-06 - accuracy: 1.0000 - val_loss: 13.7667 - val_accuracy: 0.3159
Epoch 7630/10000
1/1 [==============================] - 0s 102ms/step - loss: 5.8605e-06 - accuracy: 1.0000 - val_loss: 13.7663 - val_accuracy: 0.3159
Epoch 7631/10000
1/1 [==============================] - 0s 103ms/step - loss: 5.8577e-06 - accuracy: 1.0000 - val_loss: 13.7667 - val_accuracy: 0.3158
Epoch 7632/10000
1/1 [==============================] - 0s 106ms/step - loss: 5.8541e-06 - accuracy: 1.0000 - val_loss: 13.7681 - val_accuracy: 0.3158
Epoch 7633/10000
1/1 [==============================] - 0s 108ms/step - loss: 5.8493e-06 - accuracy: 1.0000 - val_loss: 13.7695 - val_accuracy: 0.3158
Epoch 7634/10000
1/1 [==============================] - 0s 110ms/step - loss: 5.8457e-06 - accuracy: 1.0000 - val_loss: 13.7705 - val_accuracy: 0.3158
Epoch 7635/10000
1/1 [==============================] - 0s 101ms/step - loss: 5.8414e-06 - accuracy: 1.0000 - val_loss: 13.7704 - val_accuracy: 0.3158
Epoch 7636/10000
1/1 [==============================] - 0s 104ms/step - loss: 5.8391e-06 - accuracy: 1.0000 - val_loss: 13.7703 - val_accuracy: 0.3158
Epoch 7637/10000
1/1 [==============================] - 0s 106ms/step - loss: 5.8381e-06 - accuracy: 1.0000 - val_loss: 13.7701 - val_accuracy: 0.3158
Epoch 7638/10000
1/1 [==============================] - 0s 105ms/step - loss: 5.8341e-06 - accuracy: 1.0000 - val_loss: 13.7709 - val_accuracy: 0.3158
Epoch 7639/10000
1/1 [==============================] - 0s 101ms/step - loss: 5.8300e-06 - accuracy: 1.0000 - val_loss: 13.7723 - val_accuracy: 0.3158
Epoch 7640/10000
1/1 [==============================] - 0s 109ms/step - loss: 5.8252e-06 - accuracy: 1.0000 - val_loss: 13.7737 - val_accuracy: 0.3158
Epoch 7641/10000
1/1 [==============================] - 0s 102ms/step - loss: 5.8209e-06 - accuracy: 1.0000 - val_loss: 13.7745 - val_accuracy: 0.3158
Epoch 7642/10000
1/1 [==============================] - 0s 102ms/step - loss: 5.8188e-06 - accuracy: 1.0000 - val_loss: 13.7747 - val_accuracy: 0.3158
Epoch 7643/10000
1/1 [==============================] - 0s 107ms/step - loss: 5.8155e-06 - accuracy: 1.0000 - val_loss: 13.7748 - val_accuracy: 0.3158
Epoch 7644/10000
1/1 [==============================] - 0s 114ms/step - loss: 5.8107e-06 - accuracy: 1.0000 - val_loss: 13.7751 - val_accuracy: 0.3159
Epoch 7645/10000
1/1 [==============================] - 0s 106ms/step - loss: 5.8088e-06 - accuracy: 1.0000 - val_loss: 13.7758 - val_accuracy: 0.3158
Epoch 7646/10000
1/1 [==============================] - 0s 102ms/step - loss: 5.8009e-06 - accuracy: 1.0000 - val_loss: 13.7769 - val_accuracy: 0.3158
Epoch 7647/10000
1/1 [==============================] - 0s 102ms/step - loss: 5.8023e-06 - accuracy: 1.0000 - val_loss: 13.7779 - val_accuracy: 0.3157
Epoch 7648/10000
1/1 [==============================] - 0s 103ms/step - loss: 5.7981e-06 - accuracy: 1.0000 - val_loss: 13.7784 - val_accuracy: 0.3157
Epoch 7649/10000
1/1 [==============================] - 0s 107ms/step - loss: 5.7935e-06 - accuracy: 1.0000 - val_loss: 13.7787 - val_accuracy: 0.3158
Epoch 7650/10000
1/1 [==============================] - 0s 101ms/step - loss: 5.7923e-06 - accuracy: 1.0000 - val_loss: 13.7790 - val_accuracy: 0.3157
Epoch 7651/10000
1/1 [==============================] - 0s 106ms/step - loss: 5.7868e-06 - accuracy: 1.0000 - val_loss: 13.7799 - val_accuracy: 0.3158
Epoch 7652/10000
1/1 [==============================] - 0s 109ms/step - loss: 5.7849e-06 - accuracy: 1.0000 - val_loss: 13.7810 - val_accuracy: 0.3158
Epoch 7653/10000
1/1 [==============================] - 0s 111ms/step - loss: 5.7816e-06 - accuracy: 1.0000 - val_loss: 13.7810 - val_accuracy: 0.3159
Epoch 7654/10000
1/1 [==============================] - 0s 108ms/step - loss: 5.7766e-06 - accuracy: 1.0000 - val_loss: 13.7812 - val_accuracy: 0.3158
Epoch 7655/10000
1/1 [==============================] - 0s 107ms/step - loss: 5.7742e-06 - accuracy: 1.0000 - val_loss: 13.7820 - val_accuracy: 0.3157
Epoch 7656/10000
1/1 [==============================] - 0s 110ms/step - loss: 5.7730e-06 - accuracy: 1.0000 - val_loss: 13.7830 - val_accuracy: 0.3157
Epoch 7657/10000
1/1 [==============================] - 0s 108ms/step - loss: 5.7718e-06 - accuracy: 1.0000 - val_loss: 13.7836 - val_accuracy: 0.3157
Epoch 7658/10000
1/1 [==============================] - 0s 113ms/step - loss: 5.7637e-06 - accuracy: 1.0000 - val_loss: 13.7837 - val_accuracy: 0.3158
Epoch 7659/10000
1/1 [==============================] - 0s 110ms/step - loss: 5.7599e-06 - accuracy: 1.0000 - val_loss: 13.7845 - val_accuracy: 0.3157
Epoch 7660/10000
1/1 [==============================] - 0s 109ms/step - loss: 5.7580e-06 - accuracy: 1.0000 - val_loss: 13.7846 - val_accuracy: 0.3157
Epoch 7661/10000
1/1 [==============================] - 0s 107ms/step - loss: 5.7506e-06 - accuracy: 1.0000 - val_loss: 13.7850 - val_accuracy: 0.3158
Epoch 7662/10000
1/1 [==============================] - 0s 106ms/step - loss: 5.7499e-06 - accuracy: 1.0000 - val_loss: 13.7861 - val_accuracy: 0.3157
Epoch 7663/10000
1/1 [==============================] - 0s 105ms/step - loss: 5.7470e-06 - accuracy: 1.0000 - val_loss: 13.7872 - val_accuracy: 0.3157
Epoch 7664/10000
1/1 [==============================] - 0s 113ms/step - loss: 5.7427e-06 - accuracy: 1.0000 - val_loss: 13.7876 - val_accuracy: 0.3157
Epoch 7665/10000
1/1 [==============================] - 0s 108ms/step - loss: 5.7380e-06 - accuracy: 1.0000 - val_loss: 13.7877 - val_accuracy: 0.3157
Epoch 7666/10000
1/1 [==============================] - 0s 108ms/step - loss: 5.7361e-06 - accuracy: 1.0000 - val_loss: 13.7881 - val_accuracy: 0.3157
Epoch 7667/10000
1/1 [==============================] - 0s 100ms/step - loss: 5.7327e-06 - accuracy: 1.0000 - val_loss: 13.7892 - val_accuracy: 0.3158
Epoch 7668/10000
1/1 [==============================] - 0s 114ms/step - loss: 5.7289e-06 - accuracy: 1.0000 - val_loss: 13.7904 - val_accuracy: 0.3158
Epoch 7669/10000
1/1 [==============================] - 0s 105ms/step - loss: 5.7260e-06 - accuracy: 1.0000 - val_loss: 13.7913 - val_accuracy: 0.3158
Epoch 7670/10000
1/1 [==============================] - 0s 112ms/step - loss: 5.7225e-06 - accuracy: 1.0000 - val_loss: 13.7911 - val_accuracy: 0.3159
Epoch 7671/10000
1/1 [==============================] - 0s 110ms/step - loss: 5.7189e-06 - accuracy: 1.0000 - val_loss: 13.7907 - val_accuracy: 0.3160
Epoch 7672/10000
1/1 [==============================] - 0s 107ms/step - loss: 5.7153e-06 - accuracy: 1.0000 - val_loss: 13.7914 - val_accuracy: 0.3159
Epoch 7673/10000
1/1 [==============================] - 0s 114ms/step - loss: 5.7115e-06 - accuracy: 1.0000 - val_loss: 13.7930 - val_accuracy: 0.3158
Epoch 7674/10000
1/1 [==============================] - 0s 109ms/step - loss: 5.7089e-06 - accuracy: 1.0000 - val_loss: 13.7945 - val_accuracy: 0.3158
Epoch 7675/10000
1/1 [==============================] - 0s 101ms/step - loss: 5.7048e-06 - accuracy: 1.0000 - val_loss: 13.7949 - val_accuracy: 0.3158
Epoch 7676/10000
1/1 [==============================] - 0s 104ms/step - loss: 5.7044e-06 - accuracy: 1.0000 - val_loss: 13.7947 - val_accuracy: 0.3158
Epoch 7677/10000
1/1 [==============================] - 0s 103ms/step - loss: 5.6962e-06 - accuracy: 1.0000 - val_loss: 13.7948 - val_accuracy: 0.3158
Epoch 7678/10000
1/1 [==============================] - 0s 101ms/step - loss: 5.6943e-06 - accuracy: 1.0000 - val_loss: 13.7958 - val_accuracy: 0.3159
Epoch 7679/10000
1/1 [==============================] - 0s 106ms/step - loss: 5.6910e-06 - accuracy: 1.0000 - val_loss: 13.7971 - val_accuracy: 0.3159
Epoch 7680/10000
1/1 [==============================] - 0s 103ms/step - loss: 5.6865e-06 - accuracy: 1.0000 - val_loss: 13.7979 - val_accuracy: 0.3158
Epoch 7681/10000
1/1 [==============================] - 0s 106ms/step - loss: 5.6843e-06 - accuracy: 1.0000 - val_loss: 13.7979 - val_accuracy: 0.3158
Epoch 7682/10000
1/1 [==============================] - 0s 104ms/step - loss: 5.6822e-06 - accuracy: 1.0000 - val_loss: 13.7979 - val_accuracy: 0.3158
Epoch 7683/10000
1/1 [==============================] - 0s 101ms/step - loss: 5.6762e-06 - accuracy: 1.0000 - val_loss: 13.7988 - val_accuracy: 0.3158
Epoch 7684/10000
1/1 [==============================] - 0s 103ms/step - loss: 5.6738e-06 - accuracy: 1.0000 - val_loss: 13.8002 - val_accuracy: 0.3158
Epoch 7685/10000
1/1 [==============================] - 0s 102ms/step - loss: 5.6712e-06 - accuracy: 1.0000 - val_loss: 13.8010 - val_accuracy: 0.3158
Epoch 7686/10000
1/1 [==============================] - 0s 110ms/step - loss: 5.6667e-06 - accuracy: 1.0000 - val_loss: 13.8008 - val_accuracy: 0.3160
Epoch 7687/10000
1/1 [==============================] - 0s 107ms/step - loss: 5.6600e-06 - accuracy: 1.0000 - val_loss: 13.8009 - val_accuracy: 0.3159
Epoch 7688/10000
1/1 [==============================] - 0s 102ms/step - loss: 5.6583e-06 - accuracy: 1.0000 - val_loss: 13.8017 - val_accuracy: 0.3159
Epoch 7689/10000
1/1 [==============================] - 0s 106ms/step - loss: 5.6564e-06 - accuracy: 1.0000 - val_loss: 13.8030 - val_accuracy: 0.3158
Epoch 7690/10000
1/1 [==============================] - 0s 104ms/step - loss: 5.6524e-06 - accuracy: 1.0000 - val_loss: 13.8037 - val_accuracy: 0.3158
Epoch 7691/10000
1/1 [==============================] - 0s 106ms/step - loss: 5.6488e-06 - accuracy: 1.0000 - val_loss: 13.8040 - val_accuracy: 0.3158
Epoch 7692/10000
1/1 [==============================] - 0s 101ms/step - loss: 5.6455e-06 - accuracy: 1.0000 - val_loss: 13.8036 - val_accuracy: 0.3158
Epoch 7693/10000
1/1 [==============================] - 0s 104ms/step - loss: 5.6450e-06 - accuracy: 1.0000 - val_loss: 13.8039 - val_accuracy: 0.3160
Epoch 7694/10000
1/1 [==============================] - 0s 103ms/step - loss: 5.6383e-06 - accuracy: 1.0000 - val_loss: 13.8044 - val_accuracy: 0.3160
Epoch 7695/10000
1/1 [==============================] - 0s 104ms/step - loss: 5.6362e-06 - accuracy: 1.0000 - val_loss: 13.8047 - val_accuracy: 0.3160
Epoch 7696/10000
1/1 [==============================] - 0s 102ms/step - loss: 5.6328e-06 - accuracy: 1.0000 - val_loss: 13.8058 - val_accuracy: 0.3158
Epoch 7697/10000
1/1 [==============================] - 0s 101ms/step - loss: 5.6293e-06 - accuracy: 1.0000 - val_loss: 13.8074 - val_accuracy: 0.3157
Epoch 7698/10000
1/1 [==============================] - 0s 105ms/step - loss: 5.6238e-06 - accuracy: 1.0000 - val_loss: 13.8088 - val_accuracy: 0.3159
Epoch 7699/10000
1/1 [==============================] - 0s 114ms/step - loss: 5.6226e-06 - accuracy: 1.0000 - val_loss: 13.8085 - val_accuracy: 0.3160
Epoch 7700/10000
1/1 [==============================] - 0s 114ms/step - loss: 5.6190e-06 - accuracy: 1.0000 - val_loss: 13.8082 - val_accuracy: 0.3159
Epoch 7701/10000
1/1 [==============================] - 0s 101ms/step - loss: 5.6166e-06 - accuracy: 1.0000 - val_loss: 13.8091 - val_accuracy: 0.3158
Epoch 7702/10000
1/1 [==============================] - 0s 103ms/step - loss: 5.6133e-06 - accuracy: 1.0000 - val_loss: 13.8104 - val_accuracy: 0.3158
Epoch 7703/10000
1/1 [==============================] - 0s 100ms/step - loss: 5.6107e-06 - accuracy: 1.0000 - val_loss: 13.8111 - val_accuracy: 0.3159
Epoch 7704/10000
1/1 [==============================] - 0s 101ms/step - loss: 5.6040e-06 - accuracy: 1.0000 - val_loss: 13.8117 - val_accuracy: 0.3160
Epoch 7705/10000
1/1 [==============================] - 0s 106ms/step - loss: 5.6009e-06 - accuracy: 1.0000 - val_loss: 13.8118 - val_accuracy: 0.3159
Epoch 7706/10000
1/1 [==============================] - 0s 107ms/step - loss: 5.5968e-06 - accuracy: 1.0000 - val_loss: 13.8124 - val_accuracy: 0.3158
Epoch 7707/10000
1/1 [==============================] - 0s 108ms/step - loss: 5.5930e-06 - accuracy: 1.0000 - val_loss: 13.8132 - val_accuracy: 0.3157
Epoch 7708/10000
1/1 [==============================] - 0s 105ms/step - loss: 5.5904e-06 - accuracy: 1.0000 - val_loss: 13.8140 - val_accuracy: 0.3159
Epoch 7709/10000
1/1 [==============================] - 0s 105ms/step - loss: 5.5863e-06 - accuracy: 1.0000 - val_loss: 13.8149 - val_accuracy: 0.3160
Epoch 7710/10000
1/1 [==============================] - 0s 105ms/step - loss: 5.5825e-06 - accuracy: 1.0000 - val_loss: 13.8151 - val_accuracy: 0.3160
Epoch 7711/10000
1/1 [==============================] - 0s 100ms/step - loss: 5.5794e-06 - accuracy: 1.0000 - val_loss: 13.8154 - val_accuracy: 0.3157
Epoch 7712/10000
1/1 [==============================] - 0s 101ms/step - loss: 5.5770e-06 - accuracy: 1.0000 - val_loss: 13.8161 - val_accuracy: 0.3157
Epoch 7713/10000
1/1 [==============================] - 0s 103ms/step - loss: 5.5732e-06 - accuracy: 1.0000 - val_loss: 13.8167 - val_accuracy: 0.3160
Epoch 7714/10000
1/1 [==============================] - 0s 104ms/step - loss: 5.5677e-06 - accuracy: 1.0000 - val_loss: 13.8176 - val_accuracy: 0.3160
Epoch 7715/10000
1/1 [==============================] - 0s 106ms/step - loss: 5.5646e-06 - accuracy: 1.0000 - val_loss: 13.8180 - val_accuracy: 0.3159
Epoch 7716/10000
1/1 [==============================] - 0s 103ms/step - loss: 5.5656e-06 - accuracy: 1.0000 - val_loss: 13.8183 - val_accuracy: 0.3159
Epoch 7717/10000
1/1 [==============================] - 0s 113ms/step - loss: 5.5632e-06 - accuracy: 1.0000 - val_loss: 13.8189 - val_accuracy: 0.3159
Epoch 7718/10000
1/1 [==============================] - 0s 103ms/step - loss: 5.5573e-06 - accuracy: 1.0000 - val_loss: 13.8195 - val_accuracy: 0.3159
Epoch 7719/10000
1/1 [==============================] - 0s 101ms/step - loss: 5.5522e-06 - accuracy: 1.0000 - val_loss: 13.8201 - val_accuracy: 0.3160
Epoch 7720/10000
1/1 [==============================] - 0s 102ms/step - loss: 5.5494e-06 - accuracy: 1.0000 - val_loss: 13.8209 - val_accuracy: 0.3158
Epoch 7721/10000
1/1 [==============================] - 0s 103ms/step - loss: 5.5453e-06 - accuracy: 1.0000 - val_loss: 13.8216 - val_accuracy: 0.3158
Epoch 7722/10000
1/1 [==============================] - 0s 100ms/step - loss: 5.5432e-06 - accuracy: 1.0000 - val_loss: 13.8213 - val_accuracy: 0.3159
Epoch 7723/10000
1/1 [==============================] - 0s 107ms/step - loss: 5.5365e-06 - accuracy: 1.0000 - val_loss: 13.8218 - val_accuracy: 0.3159
Epoch 7724/10000
1/1 [==============================] - 0s 100ms/step - loss: 5.5358e-06 - accuracy: 1.0000 - val_loss: 13.8234 - val_accuracy: 0.3160
Epoch 7725/10000
1/1 [==============================] - 0s 101ms/step - loss: 5.5329e-06 - accuracy: 1.0000 - val_loss: 13.8245 - val_accuracy: 0.3159
Epoch 7726/10000
1/1 [==============================] - 0s 106ms/step - loss: 5.5310e-06 - accuracy: 1.0000 - val_loss: 13.8245 - val_accuracy: 0.3159
Epoch 7727/10000
1/1 [==============================] - 0s 106ms/step - loss: 5.5232e-06 - accuracy: 1.0000 - val_loss: 13.8245 - val_accuracy: 0.3159
Epoch 7728/10000
1/1 [==============================] - 0s 103ms/step - loss: 5.5236e-06 - accuracy: 1.0000 - val_loss: 13.8253 - val_accuracy: 0.3159
Epoch 7729/10000
1/1 [==============================] - 0s 100ms/step - loss: 5.5213e-06 - accuracy: 1.0000 - val_loss: 13.8268 - val_accuracy: 0.3160
Epoch 7730/10000
1/1 [==============================] - 0s 104ms/step - loss: 5.5174e-06 - accuracy: 1.0000 - val_loss: 13.8277 - val_accuracy: 0.3160
Epoch 7731/10000
1/1 [==============================] - 0s 109ms/step - loss: 5.5151e-06 - accuracy: 1.0000 - val_loss: 13.8277 - val_accuracy: 0.3159
Epoch 7732/10000
1/1 [==============================] - 0s 100ms/step - loss: 5.5091e-06 - accuracy: 1.0000 - val_loss: 13.8282 - val_accuracy: 0.3159
Epoch 7733/10000
1/1 [==============================] - 0s 103ms/step - loss: 5.5029e-06 - accuracy: 1.0000 - val_loss: 13.8289 - val_accuracy: 0.3159
Epoch 7734/10000
1/1 [==============================] - 0s 101ms/step - loss: 5.5029e-06 - accuracy: 1.0000 - val_loss: 13.8296 - val_accuracy: 0.3160
Epoch 7735/10000
1/1 [==============================] - 0s 108ms/step - loss: 5.5022e-06 - accuracy: 1.0000 - val_loss: 13.8301 - val_accuracy: 0.3160
Epoch 7736/10000
1/1 [==============================] - 0s 105ms/step - loss: 5.5003e-06 - accuracy: 1.0000 - val_loss: 13.8302 - val_accuracy: 0.3159
Epoch 7737/10000
1/1 [==============================] - 0s 103ms/step - loss: 5.4943e-06 - accuracy: 1.0000 - val_loss: 13.8303 - val_accuracy: 0.3159
Epoch 7738/10000
1/1 [==============================] - 0s 102ms/step - loss: 5.4898e-06 - accuracy: 1.0000 - val_loss: 13.8310 - val_accuracy: 0.3159
Epoch 7739/10000
1/1 [==============================] - 0s 102ms/step - loss: 5.4867e-06 - accuracy: 1.0000 - val_loss: 13.8325 - val_accuracy: 0.3158
Epoch 7740/10000
1/1 [==============================] - 0s 101ms/step - loss: 5.4850e-06 - accuracy: 1.0000 - val_loss: 13.8337 - val_accuracy: 0.3160
Epoch 7741/10000
1/1 [==============================] - 0s 101ms/step - loss: 5.4807e-06 - accuracy: 1.0000 - val_loss: 13.8341 - val_accuracy: 0.3158
Epoch 7742/10000
1/1 [==============================] - 0s 101ms/step - loss: 5.4791e-06 - accuracy: 1.0000 - val_loss: 13.8339 - val_accuracy: 0.3159
Epoch 7743/10000
1/1 [==============================] - 0s 103ms/step - loss: 5.4757e-06 - accuracy: 1.0000 - val_loss: 13.8339 - val_accuracy: 0.3159
Epoch 7744/10000
1/1 [==============================] - 0s 103ms/step - loss: 5.4724e-06 - accuracy: 1.0000 - val_loss: 13.8349 - val_accuracy: 0.3159
Epoch 7745/10000
1/1 [==============================] - 0s 102ms/step - loss: 5.4671e-06 - accuracy: 1.0000 - val_loss: 13.8367 - val_accuracy: 0.3158
Epoch 7746/10000
1/1 [==============================] - 0s 100ms/step - loss: 5.4645e-06 - accuracy: 1.0000 - val_loss: 13.8370 - val_accuracy: 0.3158
Epoch 7747/10000
1/1 [==============================] - 0s 102ms/step - loss: 5.4640e-06 - accuracy: 1.0000 - val_loss: 13.8366 - val_accuracy: 0.3158
Epoch 7748/10000
1/1 [==============================] - 0s 106ms/step - loss: 5.4588e-06 - accuracy: 1.0000 - val_loss: 13.8365 - val_accuracy: 0.3159
Epoch 7749/10000
1/1 [==============================] - 0s 103ms/step - loss: 5.4564e-06 - accuracy: 1.0000 - val_loss: 13.8375 - val_accuracy: 0.3159
Epoch 7750/10000
1/1 [==============================] - 0s 103ms/step - loss: 5.4514e-06 - accuracy: 1.0000 - val_loss: 13.8391 - val_accuracy: 0.3159
Epoch 7751/10000
1/1 [==============================] - 0s 101ms/step - loss: 5.4454e-06 - accuracy: 1.0000 - val_loss: 13.8406 - val_accuracy: 0.3158
Epoch 7752/10000
1/1 [==============================] - 0s 100ms/step - loss: 5.4426e-06 - accuracy: 1.0000 - val_loss: 13.8407 - val_accuracy: 0.3158
Epoch 7753/10000
1/1 [==============================] - 0s 103ms/step - loss: 5.4407e-06 - accuracy: 1.0000 - val_loss: 13.8403 - val_accuracy: 0.3159
Epoch 7754/10000
1/1 [==============================] - 0s 101ms/step - loss: 5.4380e-06 - accuracy: 1.0000 - val_loss: 13.8406 - val_accuracy: 0.3159
Epoch 7755/10000
1/1 [==============================] - 0s 104ms/step - loss: 5.4326e-06 - accuracy: 1.0000 - val_loss: 13.8418 - val_accuracy: 0.3159
Epoch 7756/10000
1/1 [==============================] - 0s 104ms/step - loss: 5.4285e-06 - accuracy: 1.0000 - val_loss: 13.8428 - val_accuracy: 0.3158
Epoch 7757/10000
1/1 [==============================] - 0s 100ms/step - loss: 5.4261e-06 - accuracy: 1.0000 - val_loss: 13.8434 - val_accuracy: 0.3158
Epoch 7758/10000
1/1 [==============================] - 0s 103ms/step - loss: 5.4235e-06 - accuracy: 1.0000 - val_loss: 13.8438 - val_accuracy: 0.3158
Epoch 7759/10000
1/1 [==============================] - 0s 105ms/step - loss: 5.4197e-06 - accuracy: 1.0000 - val_loss: 13.8442 - val_accuracy: 0.3159
Epoch 7760/10000
1/1 [==============================] - 0s 102ms/step - loss: 5.4171e-06 - accuracy: 1.0000 - val_loss: 13.8445 - val_accuracy: 0.3159
Epoch 7761/10000
1/1 [==============================] - 0s 107ms/step - loss: 5.4128e-06 - accuracy: 1.0000 - val_loss: 13.8453 - val_accuracy: 0.3159
Epoch 7762/10000
1/1 [==============================] - 0s 101ms/step - loss: 5.4104e-06 - accuracy: 1.0000 - val_loss: 13.8464 - val_accuracy: 0.3159
Epoch 7763/10000
1/1 [==============================] - 0s 105ms/step - loss: 5.4087e-06 - accuracy: 1.0000 - val_loss: 13.8468 - val_accuracy: 0.3159
Epoch 7764/10000
1/1 [==============================] - 0s 100ms/step - loss: 5.4051e-06 - accuracy: 1.0000 - val_loss: 13.8468 - val_accuracy: 0.3159
Epoch 7765/10000
1/1 [==============================] - 0s 103ms/step - loss: 5.3994e-06 - accuracy: 1.0000 - val_loss: 13.8475 - val_accuracy: 0.3158
Epoch 7766/10000
1/1 [==============================] - 0s 102ms/step - loss: 5.3963e-06 - accuracy: 1.0000 - val_loss: 13.8483 - val_accuracy: 0.3158
Epoch 7767/10000
1/1 [==============================] - 0s 113ms/step - loss: 5.3944e-06 - accuracy: 1.0000 - val_loss: 13.8486 - val_accuracy: 0.3158
Epoch 7768/10000
1/1 [==============================] - 0s 104ms/step - loss: 5.3889e-06 - accuracy: 1.0000 - val_loss: 13.8492 - val_accuracy: 0.3158
Epoch 7769/10000
1/1 [==============================] - 0s 112ms/step - loss: 5.3877e-06 - accuracy: 1.0000 - val_loss: 13.8499 - val_accuracy: 0.3158
Epoch 7770/10000
1/1 [==============================] - 0s 105ms/step - loss: 5.3854e-06 - accuracy: 1.0000 - val_loss: 13.8507 - val_accuracy: 0.3159
Epoch 7771/10000
1/1 [==============================] - 0s 106ms/step - loss: 5.3834e-06 - accuracy: 1.0000 - val_loss: 13.8513 - val_accuracy: 0.3158
Epoch 7772/10000
1/1 [==============================] - 0s 101ms/step - loss: 5.3808e-06 - accuracy: 1.0000 - val_loss: 13.8513 - val_accuracy: 0.3158
Epoch 7773/10000
1/1 [==============================] - 0s 108ms/step - loss: 5.3770e-06 - accuracy: 1.0000 - val_loss: 13.8516 - val_accuracy: 0.3158
Epoch 7774/10000
1/1 [==============================] - 0s 111ms/step - loss: 5.3727e-06 - accuracy: 1.0000 - val_loss: 13.8526 - val_accuracy: 0.3157
Epoch 7775/10000
1/1 [==============================] - 0s 106ms/step - loss: 5.3706e-06 - accuracy: 1.0000 - val_loss: 13.8537 - val_accuracy: 0.3158
Epoch 7776/10000
1/1 [==============================] - 0s 105ms/step - loss: 5.3665e-06 - accuracy: 1.0000 - val_loss: 13.8548 - val_accuracy: 0.3159
Epoch 7777/10000
1/1 [==============================] - 0s 103ms/step - loss: 5.3651e-06 - accuracy: 1.0000 - val_loss: 13.8546 - val_accuracy: 0.3158
Epoch 7778/10000
1/1 [==============================] - 0s 106ms/step - loss: 5.3608e-06 - accuracy: 1.0000 - val_loss: 13.8545 - val_accuracy: 0.3158
Epoch 7779/10000
1/1 [==============================] - 0s 105ms/step - loss: 5.3575e-06 - accuracy: 1.0000 - val_loss: 13.8548 - val_accuracy: 0.3158
Epoch 7780/10000
1/1 [==============================] - 0s 105ms/step - loss: 5.3536e-06 - accuracy: 1.0000 - val_loss: 13.8556 - val_accuracy: 0.3158
Epoch 7781/10000
1/1 [==============================] - 0s 108ms/step - loss: 5.3498e-06 - accuracy: 1.0000 - val_loss: 13.8568 - val_accuracy: 0.3158
Epoch 7782/10000
1/1 [==============================] - 0s 110ms/step - loss: 5.3441e-06 - accuracy: 1.0000 - val_loss: 13.8580 - val_accuracy: 0.3158
Epoch 7783/10000
1/1 [==============================] - 0s 103ms/step - loss: 5.3424e-06 - accuracy: 1.0000 - val_loss: 13.8588 - val_accuracy: 0.3159
Epoch 7784/10000
1/1 [==============================] - 0s 105ms/step - loss: 5.3391e-06 - accuracy: 1.0000 - val_loss: 13.8590 - val_accuracy: 0.3158
Epoch 7785/10000
1/1 [==============================] - 0s 104ms/step - loss: 5.3346e-06 - accuracy: 1.0000 - val_loss: 13.8591 - val_accuracy: 0.3158
Epoch 7786/10000
1/1 [==============================] - 0s 107ms/step - loss: 5.3331e-06 - accuracy: 1.0000 - val_loss: 13.8593 - val_accuracy: 0.3158
Epoch 7787/10000
1/1 [==============================] - 0s 109ms/step - loss: 5.3312e-06 - accuracy: 1.0000 - val_loss: 13.8599 - val_accuracy: 0.3158
Epoch 7788/10000
1/1 [==============================] - 0s 109ms/step - loss: 5.3279e-06 - accuracy: 1.0000 - val_loss: 13.8609 - val_accuracy: 0.3158
Epoch 7789/10000
1/1 [==============================] - 0s 105ms/step - loss: 5.3231e-06 - accuracy: 1.0000 - val_loss: 13.8619 - val_accuracy: 0.3158
Epoch 7790/10000
1/1 [==============================] - 0s 100ms/step - loss: 5.3234e-06 - accuracy: 1.0000 - val_loss: 13.8630 - val_accuracy: 0.3159
Epoch 7791/10000
1/1 [==============================] - 0s 100ms/step - loss: 5.3196e-06 - accuracy: 1.0000 - val_loss: 13.8639 - val_accuracy: 0.3158
Epoch 7792/10000
1/1 [==============================] - 0s 106ms/step - loss: 5.3126e-06 - accuracy: 1.0000 - val_loss: 13.8636 - val_accuracy: 0.3158
Epoch 7793/10000
1/1 [==============================] - 0s 102ms/step - loss: 5.3088e-06 - accuracy: 1.0000 - val_loss: 13.8635 - val_accuracy: 0.3158
Epoch 7794/10000
1/1 [==============================] - 0s 104ms/step - loss: 5.3088e-06 - accuracy: 1.0000 - val_loss: 13.8642 - val_accuracy: 0.3158
Epoch 7795/10000
1/1 [==============================] - 0s 105ms/step - loss: 5.3055e-06 - accuracy: 1.0000 - val_loss: 13.8659 - val_accuracy: 0.3158
Epoch 7796/10000
1/1 [==============================] - 0s 102ms/step - loss: 5.3005e-06 - accuracy: 1.0000 - val_loss: 13.8672 - val_accuracy: 0.3158
Epoch 7797/10000
1/1 [==============================] - 0s 110ms/step - loss: 5.2983e-06 - accuracy: 1.0000 - val_loss: 13.8666 - val_accuracy: 0.3158
Epoch 7798/10000
1/1 [==============================] - 0s 102ms/step - loss: 5.2926e-06 - accuracy: 1.0000 - val_loss: 13.8664 - val_accuracy: 0.3158
Epoch 7799/10000
1/1 [==============================] - 0s 100ms/step - loss: 5.2917e-06 - accuracy: 1.0000 - val_loss: 13.8675 - val_accuracy: 0.3158
Epoch 7800/10000
1/1 [==============================] - 0s 103ms/step - loss: 5.2898e-06 - accuracy: 1.0000 - val_loss: 13.8690 - val_accuracy: 0.3158
Epoch 7801/10000
1/1 [==============================] - 0s 103ms/step - loss: 5.2836e-06 - accuracy: 1.0000 - val_loss: 13.8700 - val_accuracy: 0.3158
Epoch 7802/10000
1/1 [==============================] - 0s 102ms/step - loss: 5.2809e-06 - accuracy: 1.0000 - val_loss: 13.8696 - val_accuracy: 0.3158
Epoch 7803/10000
1/1 [==============================] - 0s 103ms/step - loss: 5.2778e-06 - accuracy: 1.0000 - val_loss: 13.8691 - val_accuracy: 0.3158
Epoch 7804/10000
1/1 [==============================] - 0s 106ms/step - loss: 5.2769e-06 - accuracy: 1.0000 - val_loss: 13.8697 - val_accuracy: 0.3158
Epoch 7805/10000
1/1 [==============================] - 0s 103ms/step - loss: 5.2716e-06 - accuracy: 1.0000 - val_loss: 13.8708 - val_accuracy: 0.3158
Epoch 7806/10000
1/1 [==============================] - 0s 104ms/step - loss: 5.2700e-06 - accuracy: 1.0000 - val_loss: 13.8717 - val_accuracy: 0.3158
Epoch 7807/10000
1/1 [==============================] - 0s 101ms/step - loss: 5.2659e-06 - accuracy: 1.0000 - val_loss: 13.8726 - val_accuracy: 0.3158
Epoch 7808/10000
1/1 [==============================] - 0s 109ms/step - loss: 5.2633e-06 - accuracy: 1.0000 - val_loss: 13.8731 - val_accuracy: 0.3158
Epoch 7809/10000
1/1 [==============================] - 0s 107ms/step - loss: 5.2602e-06 - accuracy: 1.0000 - val_loss: 13.8733 - val_accuracy: 0.3158
Epoch 7810/10000
1/1 [==============================] - 0s 100ms/step - loss: 5.2552e-06 - accuracy: 1.0000 - val_loss: 13.8737 - val_accuracy: 0.3158
Epoch 7811/10000
1/1 [==============================] - 0s 104ms/step - loss: 5.2540e-06 - accuracy: 1.0000 - val_loss: 13.8748 - val_accuracy: 0.3158
Epoch 7812/10000
1/1 [==============================] - 0s 105ms/step - loss: 5.2514e-06 - accuracy: 1.0000 - val_loss: 13.8760 - val_accuracy: 0.3157
Epoch 7813/10000
1/1 [==============================] - 0s 100ms/step - loss: 5.2471e-06 - accuracy: 1.0000 - val_loss: 13.8767 - val_accuracy: 0.3157
Epoch 7814/10000
1/1 [==============================] - 0s 102ms/step - loss: 5.2464e-06 - accuracy: 1.0000 - val_loss: 13.8768 - val_accuracy: 0.3157
Epoch 7815/10000
1/1 [==============================] - 0s 105ms/step - loss: 5.2402e-06 - accuracy: 1.0000 - val_loss: 13.8768 - val_accuracy: 0.3157
Epoch 7816/10000
1/1 [==============================] - 0s 106ms/step - loss: 5.2378e-06 - accuracy: 1.0000 - val_loss: 13.8775 - val_accuracy: 0.3157
Epoch 7817/10000
1/1 [==============================] - 0s 104ms/step - loss: 5.2347e-06 - accuracy: 1.0000 - val_loss: 13.8785 - val_accuracy: 0.3157
Epoch 7818/10000
1/1 [==============================] - 0s 102ms/step - loss: 5.2313e-06 - accuracy: 1.0000 - val_loss: 13.8791 - val_accuracy: 0.3158
Epoch 7819/10000
1/1 [==============================] - 0s 104ms/step - loss: 5.2292e-06 - accuracy: 1.0000 - val_loss: 13.8799 - val_accuracy: 0.3158
Epoch 7820/10000
1/1 [==============================] - 0s 106ms/step - loss: 5.2273e-06 - accuracy: 1.0000 - val_loss: 13.8804 - val_accuracy: 0.3157
Epoch 7821/10000
1/1 [==============================] - 0s 104ms/step - loss: 5.2232e-06 - accuracy: 1.0000 - val_loss: 13.8807 - val_accuracy: 0.3157
Epoch 7822/10000
1/1 [==============================] - 0s 98ms/step - loss: 5.2199e-06 - accuracy: 1.0000 - val_loss: 13.8804 - val_accuracy: 0.3158
Epoch 7823/10000
1/1 [==============================] - 0s 104ms/step - loss: 5.2158e-06 - accuracy: 1.0000 - val_loss: 13.8812 - val_accuracy: 0.3158
Epoch 7824/10000
1/1 [==============================] - 0s 103ms/step - loss: 5.2151e-06 - accuracy: 1.0000 - val_loss: 13.8831 - val_accuracy: 0.3157
Epoch 7825/10000
1/1 [==============================] - 0s 106ms/step - loss: 5.2106e-06 - accuracy: 1.0000 - val_loss: 13.8839 - val_accuracy: 0.3157
Epoch 7826/10000
1/1 [==============================] - 0s 107ms/step - loss: 5.2085e-06 - accuracy: 1.0000 - val_loss: 13.8836 - val_accuracy: 0.3157
Epoch 7827/10000
1/1 [==============================] - 0s 108ms/step - loss: 5.2032e-06 - accuracy: 1.0000 - val_loss: 13.8841 - val_accuracy: 0.3157
Epoch 7828/10000
1/1 [==============================] - 0s 108ms/step - loss: 5.1992e-06 - accuracy: 1.0000 - val_loss: 13.8854 - val_accuracy: 0.3157
Epoch 7829/10000
1/1 [==============================] - 0s 102ms/step - loss: 5.1963e-06 - accuracy: 1.0000 - val_loss: 13.8865 - val_accuracy: 0.3157
Epoch 7830/10000
1/1 [==============================] - 0s 101ms/step - loss: 5.1980e-06 - accuracy: 1.0000 - val_loss: 13.8866 - val_accuracy: 0.3158
Epoch 7831/10000
1/1 [==============================] - 0s 99ms/step - loss: 5.1927e-06 - accuracy: 1.0000 - val_loss: 13.8865 - val_accuracy: 0.3157
Epoch 7832/10000
1/1 [==============================] - 0s 100ms/step - loss: 5.1920e-06 - accuracy: 1.0000 - val_loss: 13.8870 - val_accuracy: 0.3157
Epoch 7833/10000
1/1 [==============================] - 0s 102ms/step - loss: 5.1887e-06 - accuracy: 1.0000 - val_loss: 13.8882 - val_accuracy: 0.3157
Epoch 7834/10000
1/1 [==============================] - 0s 103ms/step - loss: 5.1827e-06 - accuracy: 1.0000 - val_loss: 13.8891 - val_accuracy: 0.3157
Epoch 7835/10000
1/1 [==============================] - 0s 102ms/step - loss: 5.1808e-06 - accuracy: 1.0000 - val_loss: 13.8890 - val_accuracy: 0.3156
Epoch 7836/10000
1/1 [==============================] - 0s 105ms/step - loss: 5.1791e-06 - accuracy: 1.0000 - val_loss: 13.8892 - val_accuracy: 0.3157
Epoch 7837/10000
1/1 [==============================] - 0s 103ms/step - loss: 5.1746e-06 - accuracy: 1.0000 - val_loss: 13.8897 - val_accuracy: 0.3157
Epoch 7838/10000
1/1 [==============================] - 0s 106ms/step - loss: 5.1729e-06 - accuracy: 1.0000 - val_loss: 13.8905 - val_accuracy: 0.3157
Epoch 7839/10000
1/1 [==============================] - 0s 101ms/step - loss: 5.1701e-06 - accuracy: 1.0000 - val_loss: 13.8914 - val_accuracy: 0.3157
Epoch 7840/10000
1/1 [==============================] - 0s 103ms/step - loss: 5.1624e-06 - accuracy: 1.0000 - val_loss: 13.8927 - val_accuracy: 0.3158
Epoch 7841/10000
1/1 [==============================] - 0s 102ms/step - loss: 5.1591e-06 - accuracy: 1.0000 - val_loss: 13.8929 - val_accuracy: 0.3157
Epoch 7842/10000
1/1 [==============================] - 0s 109ms/step - loss: 5.1560e-06 - accuracy: 1.0000 - val_loss: 13.8928 - val_accuracy: 0.3157
Epoch 7843/10000
1/1 [==============================] - 0s 104ms/step - loss: 5.1539e-06 - accuracy: 1.0000 - val_loss: 13.8933 - val_accuracy: 0.3157
Epoch 7844/10000
1/1 [==============================] - 0s 101ms/step - loss: 5.1515e-06 - accuracy: 1.0000 - val_loss: 13.8946 - val_accuracy: 0.3156
Epoch 7845/10000
1/1 [==============================] - 0s 105ms/step - loss: 5.1493e-06 - accuracy: 1.0000 - val_loss: 13.8955 - val_accuracy: 0.3155
Epoch 7846/10000
1/1 [==============================] - 0s 102ms/step - loss: 5.1436e-06 - accuracy: 1.0000 - val_loss: 13.8961 - val_accuracy: 0.3157
Epoch 7847/10000
1/1 [==============================] - 0s 101ms/step - loss: 5.1407e-06 - accuracy: 1.0000 - val_loss: 13.8960 - val_accuracy: 0.3157
Epoch 7848/10000
1/1 [==============================] - 0s 107ms/step - loss: 5.1393e-06 - accuracy: 1.0000 - val_loss: 13.8966 - val_accuracy: 0.3157
Epoch 7849/10000
1/1 [==============================] - 0s 102ms/step - loss: 5.1360e-06 - accuracy: 1.0000 - val_loss: 13.8968 - val_accuracy: 0.3156
Epoch 7850/10000
1/1 [==============================] - 0s 101ms/step - loss: 5.1329e-06 - accuracy: 1.0000 - val_loss: 13.8974 - val_accuracy: 0.3156
Epoch 7851/10000
1/1 [==============================] - 0s 100ms/step - loss: 5.1276e-06 - accuracy: 1.0000 - val_loss: 13.8986 - val_accuracy: 0.3157
Epoch 7852/10000
1/1 [==============================] - 0s 99ms/step - loss: 5.1241e-06 - accuracy: 1.0000 - val_loss: 13.9000 - val_accuracy: 0.3155
Epoch 7853/10000
1/1 [==============================] - 0s 100ms/step - loss: 5.1205e-06 - accuracy: 1.0000 - val_loss: 13.9002 - val_accuracy: 0.3157
Epoch 7854/10000
1/1 [==============================] - 0s 107ms/step - loss: 5.1176e-06 - accuracy: 1.0000 - val_loss: 13.9005 - val_accuracy: 0.3157
Epoch 7855/10000
1/1 [==============================] - 0s 104ms/step - loss: 5.1164e-06 - accuracy: 1.0000 - val_loss: 13.9009 - val_accuracy: 0.3156
Epoch 7856/10000
1/1 [==============================] - 0s 105ms/step - loss: 5.1126e-06 - accuracy: 1.0000 - val_loss: 13.9016 - val_accuracy: 0.3157
Epoch 7857/10000
1/1 [==============================] - 0s 101ms/step - loss: 5.1107e-06 - accuracy: 1.0000 - val_loss: 13.9021 - val_accuracy: 0.3157
Epoch 7858/10000
1/1 [==============================] - 0s 105ms/step - loss: 5.1071e-06 - accuracy: 1.0000 - val_loss: 13.9023 - val_accuracy: 0.3157
Epoch 7859/10000
1/1 [==============================] - 0s 104ms/step - loss: 5.1031e-06 - accuracy: 1.0000 - val_loss: 13.9030 - val_accuracy: 0.3156
Epoch 7860/10000
1/1 [==============================] - 0s 106ms/step - loss: 5.0995e-06 - accuracy: 1.0000 - val_loss: 13.9045 - val_accuracy: 0.3156
Epoch 7861/10000
1/1 [==============================] - 0s 108ms/step - loss: 5.0988e-06 - accuracy: 1.0000 - val_loss: 13.9054 - val_accuracy: 0.3155
Epoch 7862/10000
1/1 [==============================] - 0s 100ms/step - loss: 5.0943e-06 - accuracy: 1.0000 - val_loss: 13.9056 - val_accuracy: 0.3156
Epoch 7863/10000
1/1 [==============================] - 0s 103ms/step - loss: 5.0902e-06 - accuracy: 1.0000 - val_loss: 13.9059 - val_accuracy: 0.3155
Epoch 7864/10000
1/1 [==============================] - 0s 100ms/step - loss: 5.0869e-06 - accuracy: 1.0000 - val_loss: 13.9062 - val_accuracy: 0.3156
Epoch 7865/10000
1/1 [==============================] - 0s 103ms/step - loss: 5.0857e-06 - accuracy: 1.0000 - val_loss: 13.9067 - val_accuracy: 0.3157
Epoch 7866/10000
1/1 [==============================] - 0s 108ms/step - loss: 5.0826e-06 - accuracy: 1.0000 - val_loss: 13.9079 - val_accuracy: 0.3156
Epoch 7867/10000
1/1 [==============================] - 0s 104ms/step - loss: 5.0809e-06 - accuracy: 1.0000 - val_loss: 13.9084 - val_accuracy: 0.3156
Epoch 7868/10000
1/1 [==============================] - 0s 103ms/step - loss: 5.0764e-06 - accuracy: 1.0000 - val_loss: 13.9083 - val_accuracy: 0.3156
Epoch 7869/10000
1/1 [==============================] - 0s 100ms/step - loss: 5.0726e-06 - accuracy: 1.0000 - val_loss: 13.9092 - val_accuracy: 0.3156
Epoch 7870/10000
1/1 [==============================] - 0s 106ms/step - loss: 5.0714e-06 - accuracy: 1.0000 - val_loss: 13.9107 - val_accuracy: 0.3156
Epoch 7871/10000
1/1 [==============================] - 0s 109ms/step - loss: 5.0706e-06 - accuracy: 1.0000 - val_loss: 13.9107 - val_accuracy: 0.3155
Epoch 7872/10000
1/1 [==============================] - 0s 108ms/step - loss: 5.0640e-06 - accuracy: 1.0000 - val_loss: 13.9102 - val_accuracy: 0.3156
Epoch 7873/10000
1/1 [==============================] - 0s 109ms/step - loss: 5.0652e-06 - accuracy: 1.0000 - val_loss: 13.9104 - val_accuracy: 0.3155
Epoch 7874/10000
1/1 [==============================] - 0s 107ms/step - loss: 5.0592e-06 - accuracy: 1.0000 - val_loss: 13.9115 - val_accuracy: 0.3155
Epoch 7875/10000
1/1 [==============================] - 0s 104ms/step - loss: 5.0568e-06 - accuracy: 1.0000 - val_loss: 13.9129 - val_accuracy: 0.3155
Epoch 7876/10000
1/1 [==============================] - 0s 100ms/step - loss: 5.0499e-06 - accuracy: 1.0000 - val_loss: 13.9140 - val_accuracy: 0.3156
Epoch 7877/10000
1/1 [==============================] - 0s 103ms/step - loss: 5.0480e-06 - accuracy: 1.0000 - val_loss: 13.9142 - val_accuracy: 0.3154
Epoch 7878/10000
1/1 [==============================] - 0s 108ms/step - loss: 5.0466e-06 - accuracy: 1.0000 - val_loss: 13.9141 - val_accuracy: 0.3156
Epoch 7879/10000
1/1 [==============================] - 0s 102ms/step - loss: 5.0428e-06 - accuracy: 1.0000 - val_loss: 13.9145 - val_accuracy: 0.3155
Epoch 7880/10000
1/1 [==============================] - 0s 103ms/step - loss: 5.0411e-06 - accuracy: 1.0000 - val_loss: 13.9153 - val_accuracy: 0.3155
Epoch 7881/10000
1/1 [==============================] - 0s 104ms/step - loss: 5.0366e-06 - accuracy: 1.0000 - val_loss: 13.9162 - val_accuracy: 0.3156
Epoch 7882/10000
1/1 [==============================] - 0s 111ms/step - loss: 5.0339e-06 - accuracy: 1.0000 - val_loss: 13.9173 - val_accuracy: 0.3156
Epoch 7883/10000
1/1 [==============================] - 0s 108ms/step - loss: 5.0304e-06 - accuracy: 1.0000 - val_loss: 13.9174 - val_accuracy: 0.3155
Epoch 7884/10000
1/1 [==============================] - 0s 106ms/step - loss: 5.0253e-06 - accuracy: 1.0000 - val_loss: 13.9175 - val_accuracy: 0.3155
Epoch 7885/10000
1/1 [==============================] - 0s 104ms/step - loss: 5.0234e-06 - accuracy: 1.0000 - val_loss: 13.9183 - val_accuracy: 0.3154
Epoch 7886/10000
1/1 [==============================] - 0s 108ms/step - loss: 5.0168e-06 - accuracy: 1.0000 - val_loss: 13.9193 - val_accuracy: 0.3156
Epoch 7887/10000
1/1 [==============================] - 0s 112ms/step - loss: 5.0163e-06 - accuracy: 1.0000 - val_loss: 13.9200 - val_accuracy: 0.3156
Epoch 7888/10000
1/1 [==============================] - 0s 113ms/step - loss: 5.0139e-06 - accuracy: 1.0000 - val_loss: 13.9203 - val_accuracy: 0.3155
Epoch 7889/10000
1/1 [==============================] - 0s 114ms/step - loss: 5.0125e-06 - accuracy: 1.0000 - val_loss: 13.9211 - val_accuracy: 0.3155
Epoch 7890/10000
1/1 [==============================] - 0s 113ms/step - loss: 5.0087e-06 - accuracy: 1.0000 - val_loss: 13.9221 - val_accuracy: 0.3155
Epoch 7891/10000
1/1 [==============================] - 0s 112ms/step - loss: 5.0053e-06 - accuracy: 1.0000 - val_loss: 13.9220 - val_accuracy: 0.3156
Epoch 7892/10000
1/1 [==============================] - 0s 104ms/step - loss: 5.0025e-06 - accuracy: 1.0000 - val_loss: 13.9221 - val_accuracy: 0.3156
Epoch 7893/10000
1/1 [==============================] - 0s 109ms/step - loss: 4.9989e-06 - accuracy: 1.0000 - val_loss: 13.9232 - val_accuracy: 0.3156
Epoch 7894/10000
1/1 [==============================] - 0s 112ms/step - loss: 4.9972e-06 - accuracy: 1.0000 - val_loss: 13.9248 - val_accuracy: 0.3156
Epoch 7895/10000
1/1 [==============================] - 0s 111ms/step - loss: 4.9953e-06 - accuracy: 1.0000 - val_loss: 13.9250 - val_accuracy: 0.3155
Epoch 7896/10000
1/1 [==============================] - 0s 104ms/step - loss: 4.9910e-06 - accuracy: 1.0000 - val_loss: 13.9246 - val_accuracy: 0.3154
Epoch 7897/10000
1/1 [==============================] - 0s 113ms/step - loss: 4.9874e-06 - accuracy: 1.0000 - val_loss: 13.9251 - val_accuracy: 0.3154
Epoch 7898/10000
1/1 [==============================] - 0s 110ms/step - loss: 4.9841e-06 - accuracy: 1.0000 - val_loss: 13.9255 - val_accuracy: 0.3154
Epoch 7899/10000
1/1 [==============================] - 0s 106ms/step - loss: 4.9817e-06 - accuracy: 1.0000 - val_loss: 13.9258 - val_accuracy: 0.3156
Epoch 7900/10000
1/1 [==============================] - 0s 103ms/step - loss: 4.9781e-06 - accuracy: 1.0000 - val_loss: 13.9266 - val_accuracy: 0.3157
Epoch 7901/10000
1/1 [==============================] - 0s 112ms/step - loss: 4.9772e-06 - accuracy: 1.0000 - val_loss: 13.9281 - val_accuracy: 0.3156
Epoch 7902/10000
1/1 [==============================] - 0s 108ms/step - loss: 4.9698e-06 - accuracy: 1.0000 - val_loss: 13.9293 - val_accuracy: 0.3156
Epoch 7903/10000
1/1 [==============================] - 0s 103ms/step - loss: 4.9698e-06 - accuracy: 1.0000 - val_loss: 13.9296 - val_accuracy: 0.3154
Epoch 7904/10000
1/1 [==============================] - 0s 101ms/step - loss: 4.9662e-06 - accuracy: 1.0000 - val_loss: 13.9299 - val_accuracy: 0.3155
Epoch 7905/10000
1/1 [==============================] - 0s 102ms/step - loss: 4.9634e-06 - accuracy: 1.0000 - val_loss: 13.9305 - val_accuracy: 0.3155
Epoch 7906/10000
1/1 [==============================] - 0s 109ms/step - loss: 4.9607e-06 - accuracy: 1.0000 - val_loss: 13.9307 - val_accuracy: 0.3155
Epoch 7907/10000
1/1 [==============================] - 0s 103ms/step - loss: 4.9576e-06 - accuracy: 1.0000 - val_loss: 13.9315 - val_accuracy: 0.3155
Epoch 7908/10000
1/1 [==============================] - 0s 103ms/step - loss: 4.9553e-06 - accuracy: 1.0000 - val_loss: 13.9327 - val_accuracy: 0.3155
Epoch 7909/10000
1/1 [==============================] - 0s 107ms/step - loss: 4.9514e-06 - accuracy: 1.0000 - val_loss: 13.9331 - val_accuracy: 0.3155
Epoch 7910/10000
1/1 [==============================] - 0s 101ms/step - loss: 4.9498e-06 - accuracy: 1.0000 - val_loss: 13.9332 - val_accuracy: 0.3155
Epoch 7911/10000
1/1 [==============================] - 0s 107ms/step - loss: 4.9462e-06 - accuracy: 1.0000 - val_loss: 13.9337 - val_accuracy: 0.3156
Epoch 7912/10000
1/1 [==============================] - 0s 114ms/step - loss: 4.9450e-06 - accuracy: 1.0000 - val_loss: 13.9349 - val_accuracy: 0.3155
Epoch 7913/10000
1/1 [==============================] - 0s 108ms/step - loss: 4.9369e-06 - accuracy: 1.0000 - val_loss: 13.9358 - val_accuracy: 0.3155
Epoch 7914/10000
1/1 [==============================] - 0s 107ms/step - loss: 4.9359e-06 - accuracy: 1.0000 - val_loss: 13.9364 - val_accuracy: 0.3155
Epoch 7915/10000
1/1 [==============================] - 0s 101ms/step - loss: 4.9359e-06 - accuracy: 1.0000 - val_loss: 13.9365 - val_accuracy: 0.3155
Epoch 7916/10000
1/1 [==============================] - 0s 106ms/step - loss: 4.9331e-06 - accuracy: 1.0000 - val_loss: 13.9370 - val_accuracy: 0.3155
Epoch 7917/10000
1/1 [==============================] - 0s 108ms/step - loss: 4.9281e-06 - accuracy: 1.0000 - val_loss: 13.9374 - val_accuracy: 0.3156
Epoch 7918/10000
1/1 [==============================] - 0s 102ms/step - loss: 4.9245e-06 - accuracy: 1.0000 - val_loss: 13.9380 - val_accuracy: 0.3155
Epoch 7919/10000
1/1 [==============================] - 0s 102ms/step - loss: 4.9212e-06 - accuracy: 1.0000 - val_loss: 13.9392 - val_accuracy: 0.3155
Epoch 7920/10000
1/1 [==============================] - 0s 104ms/step - loss: 4.9216e-06 - accuracy: 1.0000 - val_loss: 13.9397 - val_accuracy: 0.3155
Epoch 7921/10000
1/1 [==============================] - 0s 104ms/step - loss: 4.9159e-06 - accuracy: 1.0000 - val_loss: 13.9400 - val_accuracy: 0.3156
Epoch 7922/10000
1/1 [==============================] - 0s 103ms/step - loss: 4.9126e-06 - accuracy: 1.0000 - val_loss: 13.9409 - val_accuracy: 0.3156
Epoch 7923/10000
1/1 [==============================] - 0s 106ms/step - loss: 4.9121e-06 - accuracy: 1.0000 - val_loss: 13.9412 - val_accuracy: 0.3156
Epoch 7924/10000
1/1 [==============================] - 0s 101ms/step - loss: 4.9073e-06 - accuracy: 1.0000 - val_loss: 13.9416 - val_accuracy: 0.3156
Epoch 7925/10000
1/1 [==============================] - 0s 103ms/step - loss: 4.9059e-06 - accuracy: 1.0000 - val_loss: 13.9421 - val_accuracy: 0.3155
Epoch 7926/10000
1/1 [==============================] - 0s 108ms/step - loss: 4.9016e-06 - accuracy: 1.0000 - val_loss: 13.9426 - val_accuracy: 0.3156
Epoch 7927/10000
1/1 [==============================] - 0s 100ms/step - loss: 4.8990e-06 - accuracy: 1.0000 - val_loss: 13.9437 - val_accuracy: 0.3154
Epoch 7928/10000
1/1 [==============================] - 0s 101ms/step - loss: 4.8988e-06 - accuracy: 1.0000 - val_loss: 13.9447 - val_accuracy: 0.3154
Epoch 7929/10000
1/1 [==============================] - 0s 105ms/step - loss: 4.8940e-06 - accuracy: 1.0000 - val_loss: 13.9448 - val_accuracy: 0.3154
Epoch 7930/10000
1/1 [==============================] - 0s 102ms/step - loss: 4.8911e-06 - accuracy: 1.0000 - val_loss: 13.9448 - val_accuracy: 0.3156
Epoch 7931/10000
1/1 [==============================] - 0s 102ms/step - loss: 4.8842e-06 - accuracy: 1.0000 - val_loss: 13.9455 - val_accuracy: 0.3155
Epoch 7932/10000
1/1 [==============================] - 0s 105ms/step - loss: 4.8852e-06 - accuracy: 1.0000 - val_loss: 13.9465 - val_accuracy: 0.3155
Epoch 7933/10000
1/1 [==============================] - 0s 100ms/step - loss: 4.8809e-06 - accuracy: 1.0000 - val_loss: 13.9475 - val_accuracy: 0.3154
Epoch 7934/10000
1/1 [==============================] - 0s 103ms/step - loss: 4.8773e-06 - accuracy: 1.0000 - val_loss: 13.9479 - val_accuracy: 0.3155
Epoch 7935/10000
1/1 [==============================] - 0s 101ms/step - loss: 4.8761e-06 - accuracy: 1.0000 - val_loss: 13.9481 - val_accuracy: 0.3155
Epoch 7936/10000
1/1 [==============================] - 0s 104ms/step - loss: 4.8730e-06 - accuracy: 1.0000 - val_loss: 13.9481 - val_accuracy: 0.3156
Epoch 7937/10000
1/1 [==============================] - 0s 109ms/step - loss: 4.8675e-06 - accuracy: 1.0000 - val_loss: 13.9488 - val_accuracy: 0.3156
Epoch 7938/10000
1/1 [==============================] - 0s 100ms/step - loss: 4.8654e-06 - accuracy: 1.0000 - val_loss: 13.9502 - val_accuracy: 0.3155
Epoch 7939/10000
1/1 [==============================] - 0s 102ms/step - loss: 4.8654e-06 - accuracy: 1.0000 - val_loss: 13.9513 - val_accuracy: 0.3157
Epoch 7940/10000
1/1 [==============================] - 0s 106ms/step - loss: 4.8604e-06 - accuracy: 1.0000 - val_loss: 13.9511 - val_accuracy: 0.3156
Epoch 7941/10000
1/1 [==============================] - 0s 107ms/step - loss: 4.8568e-06 - accuracy: 1.0000 - val_loss: 13.9510 - val_accuracy: 0.3154
Epoch 7942/10000
1/1 [==============================] - 0s 104ms/step - loss: 4.8551e-06 - accuracy: 1.0000 - val_loss: 13.9520 - val_accuracy: 0.3154
Epoch 7943/10000
1/1 [==============================] - 0s 108ms/step - loss: 4.8520e-06 - accuracy: 1.0000 - val_loss: 13.9532 - val_accuracy: 0.3154
Epoch 7944/10000
1/1 [==============================] - 0s 101ms/step - loss: 4.8504e-06 - accuracy: 1.0000 - val_loss: 13.9539 - val_accuracy: 0.3155
Epoch 7945/10000
1/1 [==============================] - 0s 106ms/step - loss: 4.8458e-06 - accuracy: 1.0000 - val_loss: 13.9540 - val_accuracy: 0.3156
Epoch 7946/10000
1/1 [==============================] - 0s 101ms/step - loss: 4.8449e-06 - accuracy: 1.0000 - val_loss: 13.9543 - val_accuracy: 0.3157
Epoch 7947/10000
1/1 [==============================] - 0s 102ms/step - loss: 4.8401e-06 - accuracy: 1.0000 - val_loss: 13.9547 - val_accuracy: 0.3157
Epoch 7948/10000
1/1 [==============================] - 0s 103ms/step - loss: 4.8389e-06 - accuracy: 1.0000 - val_loss: 13.9554 - val_accuracy: 0.3157
Epoch 7949/10000
1/1 [==============================] - 0s 106ms/step - loss: 4.8370e-06 - accuracy: 1.0000 - val_loss: 13.9564 - val_accuracy: 0.3156
Epoch 7950/10000
1/1 [==============================] - 0s 105ms/step - loss: 4.8337e-06 - accuracy: 1.0000 - val_loss: 13.9576 - val_accuracy: 0.3155
Epoch 7951/10000
1/1 [==============================] - 0s 105ms/step - loss: 4.8291e-06 - accuracy: 1.0000 - val_loss: 13.9584 - val_accuracy: 0.3155
Epoch 7952/10000
1/1 [==============================] - 0s 104ms/step - loss: 4.8284e-06 - accuracy: 1.0000 - val_loss: 13.9584 - val_accuracy: 0.3154
Epoch 7953/10000
1/1 [==============================] - 0s 102ms/step - loss: 4.8241e-06 - accuracy: 1.0000 - val_loss: 13.9586 - val_accuracy: 0.3155
Epoch 7954/10000
1/1 [==============================] - 0s 110ms/step - loss: 4.8210e-06 - accuracy: 1.0000 - val_loss: 13.9596 - val_accuracy: 0.3155
Epoch 7955/10000
1/1 [==============================] - 0s 103ms/step - loss: 4.8177e-06 - accuracy: 1.0000 - val_loss: 13.9607 - val_accuracy: 0.3156
Epoch 7956/10000
1/1 [==============================] - 0s 102ms/step - loss: 4.8163e-06 - accuracy: 1.0000 - val_loss: 13.9605 - val_accuracy: 0.3155
Epoch 7957/10000
1/1 [==============================] - 0s 100ms/step - loss: 4.8120e-06 - accuracy: 1.0000 - val_loss: 13.9604 - val_accuracy: 0.3156
Epoch 7958/10000
1/1 [==============================] - 0s 108ms/step - loss: 4.8091e-06 - accuracy: 1.0000 - val_loss: 13.9614 - val_accuracy: 0.3155
Epoch 7959/10000
1/1 [==============================] - 0s 104ms/step - loss: 4.8060e-06 - accuracy: 1.0000 - val_loss: 13.9630 - val_accuracy: 0.3155
Epoch 7960/10000
1/1 [==============================] - 0s 106ms/step - loss: 4.8022e-06 - accuracy: 1.0000 - val_loss: 13.9636 - val_accuracy: 0.3155
Epoch 7961/10000
1/1 [==============================] - 0s 108ms/step - loss: 4.8008e-06 - accuracy: 1.0000 - val_loss: 13.9636 - val_accuracy: 0.3155
Epoch 7962/10000
1/1 [==============================] - 0s 102ms/step - loss: 4.7989e-06 - accuracy: 1.0000 - val_loss: 13.9636 - val_accuracy: 0.3155
Epoch 7963/10000
1/1 [==============================] - 0s 102ms/step - loss: 4.7929e-06 - accuracy: 1.0000 - val_loss: 13.9643 - val_accuracy: 0.3155
Epoch 7964/10000
1/1 [==============================] - 0s 104ms/step - loss: 4.7900e-06 - accuracy: 1.0000 - val_loss: 13.9655 - val_accuracy: 0.3156
Epoch 7965/10000
1/1 [==============================] - 0s 103ms/step - loss: 4.7896e-06 - accuracy: 1.0000 - val_loss: 13.9662 - val_accuracy: 0.3157
Epoch 7966/10000
1/1 [==============================] - 0s 101ms/step - loss: 4.7850e-06 - accuracy: 1.0000 - val_loss: 13.9667 - val_accuracy: 0.3156
Epoch 7967/10000
1/1 [==============================] - 0s 108ms/step - loss: 4.7834e-06 - accuracy: 1.0000 - val_loss: 13.9670 - val_accuracy: 0.3156
Epoch 7968/10000
1/1 [==============================] - 0s 100ms/step - loss: 4.7798e-06 - accuracy: 1.0000 - val_loss: 13.9676 - val_accuracy: 0.3156
Epoch 7969/10000
1/1 [==============================] - 0s 105ms/step - loss: 4.7793e-06 - accuracy: 1.0000 - val_loss: 13.9679 - val_accuracy: 0.3156
Epoch 7970/10000
1/1 [==============================] - 0s 103ms/step - loss: 4.7755e-06 - accuracy: 1.0000 - val_loss: 13.9682 - val_accuracy: 0.3155
Epoch 7971/10000
1/1 [==============================] - 0s 109ms/step - loss: 4.7724e-06 - accuracy: 1.0000 - val_loss: 13.9690 - val_accuracy: 0.3157
Epoch 7972/10000
1/1 [==============================] - 0s 104ms/step - loss: 4.7688e-06 - accuracy: 1.0000 - val_loss: 13.9702 - val_accuracy: 0.3157
Epoch 7973/10000
1/1 [==============================] - 0s 102ms/step - loss: 4.7648e-06 - accuracy: 1.0000 - val_loss: 13.9713 - val_accuracy: 0.3156
Epoch 7974/10000
1/1 [==============================] - 0s 100ms/step - loss: 4.7660e-06 - accuracy: 1.0000 - val_loss: 13.9712 - val_accuracy: 0.3157
Epoch 7975/10000
1/1 [==============================] - 0s 102ms/step - loss: 4.7609e-06 - accuracy: 1.0000 - val_loss: 13.9712 - val_accuracy: 0.3155
Epoch 7976/10000
1/1 [==============================] - 0s 102ms/step - loss: 4.7569e-06 - accuracy: 1.0000 - val_loss: 13.9719 - val_accuracy: 0.3155
Epoch 7977/10000
1/1 [==============================] - 0s 108ms/step - loss: 4.7559e-06 - accuracy: 1.0000 - val_loss: 13.9732 - val_accuracy: 0.3155
Epoch 7978/10000
1/1 [==============================] - 0s 101ms/step - loss: 4.7516e-06 - accuracy: 1.0000 - val_loss: 13.9745 - val_accuracy: 0.3155
Epoch 7979/10000
1/1 [==============================] - 0s 107ms/step - loss: 4.7488e-06 - accuracy: 1.0000 - val_loss: 13.9751 - val_accuracy: 0.3156
Epoch 7980/10000
1/1 [==============================] - 0s 105ms/step - loss: 4.7462e-06 - accuracy: 1.0000 - val_loss: 13.9750 - val_accuracy: 0.3156
Epoch 7981/10000
1/1 [==============================] - 0s 103ms/step - loss: 4.7426e-06 - accuracy: 1.0000 - val_loss: 13.9748 - val_accuracy: 0.3156
Epoch 7982/10000
1/1 [==============================] - 0s 102ms/step - loss: 4.7414e-06 - accuracy: 1.0000 - val_loss: 13.9755 - val_accuracy: 0.3156
Epoch 7983/10000
1/1 [==============================] - 0s 105ms/step - loss: 4.7388e-06 - accuracy: 1.0000 - val_loss: 13.9771 - val_accuracy: 0.3156
Epoch 7984/10000
1/1 [==============================] - 0s 102ms/step - loss: 4.7373e-06 - accuracy: 1.0000 - val_loss: 13.9779 - val_accuracy: 0.3156
Epoch 7985/10000
1/1 [==============================] - 0s 109ms/step - loss: 4.7357e-06 - accuracy: 1.0000 - val_loss: 13.9773 - val_accuracy: 0.3155
Epoch 7986/10000
1/1 [==============================] - 0s 105ms/step - loss: 4.7297e-06 - accuracy: 1.0000 - val_loss: 13.9773 - val_accuracy: 0.3156
Epoch 7987/10000
1/1 [==============================] - 0s 101ms/step - loss: 4.7276e-06 - accuracy: 1.0000 - val_loss: 13.9779 - val_accuracy: 0.3155
Epoch 7988/10000
1/1 [==============================] - 0s 105ms/step - loss: 4.7276e-06 - accuracy: 1.0000 - val_loss: 13.9789 - val_accuracy: 0.3155
Epoch 7989/10000
1/1 [==============================] - 0s 105ms/step - loss: 4.7218e-06 - accuracy: 1.0000 - val_loss: 13.9800 - val_accuracy: 0.3155
Epoch 7990/10000
1/1 [==============================] - 0s 104ms/step - loss: 4.7197e-06 - accuracy: 1.0000 - val_loss: 13.9807 - val_accuracy: 0.3157
Epoch 7991/10000
1/1 [==============================] - 0s 107ms/step - loss: 4.7180e-06 - accuracy: 1.0000 - val_loss: 13.9817 - val_accuracy: 0.3156
Epoch 7992/10000
1/1 [==============================] - 0s 100ms/step - loss: 4.7145e-06 - accuracy: 1.0000 - val_loss: 13.9816 - val_accuracy: 0.3156
Epoch 7993/10000
1/1 [==============================] - 0s 108ms/step - loss: 4.7111e-06 - accuracy: 1.0000 - val_loss: 13.9817 - val_accuracy: 0.3157
Epoch 7994/10000
1/1 [==============================] - 0s 105ms/step - loss: 4.7102e-06 - accuracy: 1.0000 - val_loss: 13.9823 - val_accuracy: 0.3157
Epoch 7995/10000
1/1 [==============================] - 0s 107ms/step - loss: 4.7059e-06 - accuracy: 1.0000 - val_loss: 13.9832 - val_accuracy: 0.3156
Epoch 7996/10000
1/1 [==============================] - 0s 105ms/step - loss: 4.7040e-06 - accuracy: 1.0000 - val_loss: 13.9837 - val_accuracy: 0.3156
Epoch 7997/10000
1/1 [==============================] - 0s 109ms/step - loss: 4.6987e-06 - accuracy: 1.0000 - val_loss: 13.9848 - val_accuracy: 0.3157
Epoch 7998/10000
1/1 [==============================] - 0s 113ms/step - loss: 4.6961e-06 - accuracy: 1.0000 - val_loss: 13.9860 - val_accuracy: 0.3155
Epoch 7999/10000
1/1 [==============================] - 0s 105ms/step - loss: 4.6944e-06 - accuracy: 1.0000 - val_loss: 13.9865 - val_accuracy: 0.3155
Epoch 8000/10000
1/1 [==============================] - 0s 109ms/step - loss: 4.6889e-06 - accuracy: 1.0000 - val_loss: 13.9864 - val_accuracy: 0.3156
Epoch 8001/10000
1/1 [==============================] - 0s 112ms/step - loss: 4.6870e-06 - accuracy: 1.0000 - val_loss: 13.9872 - val_accuracy: 0.3158
Epoch 8002/10000
1/1 [==============================] - 0s 103ms/step - loss: 4.6832e-06 - accuracy: 1.0000 - val_loss: 13.9883 - val_accuracy: 0.3157
Epoch 8003/10000
1/1 [==============================] - 0s 107ms/step - loss: 4.6804e-06 - accuracy: 1.0000 - val_loss: 13.9888 - val_accuracy: 0.3157
Epoch 8004/10000
1/1 [==============================] - 0s 106ms/step - loss: 4.6823e-06 - accuracy: 1.0000 - val_loss: 13.9888 - val_accuracy: 0.3157
Epoch 8005/10000
1/1 [==============================] - 0s 106ms/step - loss: 4.6758e-06 - accuracy: 1.0000 - val_loss: 13.9891 - val_accuracy: 0.3158
Epoch 8006/10000
1/1 [==============================] - 0s 110ms/step - loss: 4.6732e-06 - accuracy: 1.0000 - val_loss: 13.9902 - val_accuracy: 0.3155
Epoch 8007/10000
1/1 [==============================] - 0s 109ms/step - loss: 4.6727e-06 - accuracy: 1.0000 - val_loss: 13.9914 - val_accuracy: 0.3155
Epoch 8008/10000
1/1 [==============================] - 0s 111ms/step - loss: 4.6675e-06 - accuracy: 1.0000 - val_loss: 13.9916 - val_accuracy: 0.3156
Epoch 8009/10000
1/1 [==============================] - 0s 109ms/step - loss: 4.6644e-06 - accuracy: 1.0000 - val_loss: 13.9917 - val_accuracy: 0.3157
Epoch 8010/10000
1/1 [==============================] - 0s 105ms/step - loss: 4.6639e-06 - accuracy: 1.0000 - val_loss: 13.9927 - val_accuracy: 0.3155
Epoch 8011/10000
1/1 [==============================] - 0s 111ms/step - loss: 4.6613e-06 - accuracy: 1.0000 - val_loss: 13.9934 - val_accuracy: 0.3156
Epoch 8012/10000
1/1 [==============================] - 0s 108ms/step - loss: 4.6577e-06 - accuracy: 1.0000 - val_loss: 13.9934 - val_accuracy: 0.3154
Epoch 8013/10000
1/1 [==============================] - 0s 106ms/step - loss: 4.6556e-06 - accuracy: 1.0000 - val_loss: 13.9929 - val_accuracy: 0.3157
Epoch 8014/10000
1/1 [==============================] - 0s 119ms/step - loss: 4.6520e-06 - accuracy: 1.0000 - val_loss: 13.9933 - val_accuracy: 0.3157
Epoch 8015/10000
1/1 [==============================] - 0s 106ms/step - loss: 4.6487e-06 - accuracy: 1.0000 - val_loss: 13.9948 - val_accuracy: 0.3155
Epoch 8016/10000
1/1 [==============================] - 0s 108ms/step - loss: 4.6475e-06 - accuracy: 1.0000 - val_loss: 13.9957 - val_accuracy: 0.3158
Epoch 8017/10000
1/1 [==============================] - 0s 103ms/step - loss: 4.6434e-06 - accuracy: 1.0000 - val_loss: 13.9967 - val_accuracy: 0.3158
Epoch 8018/10000
1/1 [==============================] - 0s 105ms/step - loss: 4.6394e-06 - accuracy: 1.0000 - val_loss: 13.9980 - val_accuracy: 0.3156
Epoch 8019/10000
1/1 [==============================] - 0s 103ms/step - loss: 4.6374e-06 - accuracy: 1.0000 - val_loss: 13.9981 - val_accuracy: 0.3154
Epoch 8020/10000
1/1 [==============================] - 0s 104ms/step - loss: 4.6351e-06 - accuracy: 1.0000 - val_loss: 13.9974 - val_accuracy: 0.3156
Epoch 8021/10000
1/1 [==============================] - 0s 103ms/step - loss: 4.6334e-06 - accuracy: 1.0000 - val_loss: 13.9971 - val_accuracy: 0.3158
Epoch 8022/10000
1/1 [==============================] - 0s 101ms/step - loss: 4.6293e-06 - accuracy: 1.0000 - val_loss: 13.9981 - val_accuracy: 0.3158
Epoch 8023/10000
1/1 [==============================] - 0s 105ms/step - loss: 4.6253e-06 - accuracy: 1.0000 - val_loss: 13.9995 - val_accuracy: 0.3156
Epoch 8024/10000
1/1 [==============================] - 0s 108ms/step - loss: 4.6241e-06 - accuracy: 1.0000 - val_loss: 14.0007 - val_accuracy: 0.3155
Epoch 8025/10000
1/1 [==============================] - 0s 101ms/step - loss: 4.6203e-06 - accuracy: 1.0000 - val_loss: 14.0015 - val_accuracy: 0.3156
Epoch 8026/10000
1/1 [==============================] - 0s 100ms/step - loss: 4.6167e-06 - accuracy: 1.0000 - val_loss: 14.0024 - val_accuracy: 0.3157
Epoch 8027/10000
1/1 [==============================] - 0s 106ms/step - loss: 4.6148e-06 - accuracy: 1.0000 - val_loss: 14.0029 - val_accuracy: 0.3155
Epoch 8028/10000
1/1 [==============================] - 0s 105ms/step - loss: 4.6124e-06 - accuracy: 1.0000 - val_loss: 14.0029 - val_accuracy: 0.3155
Epoch 8029/10000
1/1 [==============================] - 0s 105ms/step - loss: 4.6079e-06 - accuracy: 1.0000 - val_loss: 14.0027 - val_accuracy: 0.3158
Epoch 8030/10000
1/1 [==============================] - 0s 100ms/step - loss: 4.6074e-06 - accuracy: 1.0000 - val_loss: 14.0038 - val_accuracy: 0.3158
Epoch 8031/10000
1/1 [==============================] - 0s 100ms/step - loss: 4.6048e-06 - accuracy: 1.0000 - val_loss: 14.0055 - val_accuracy: 0.3157
Epoch 8032/10000
1/1 [==============================] - 0s 103ms/step - loss: 4.6000e-06 - accuracy: 1.0000 - val_loss: 14.0064 - val_accuracy: 0.3154
Epoch 8033/10000
1/1 [==============================] - 0s 101ms/step - loss: 4.5972e-06 - accuracy: 1.0000 - val_loss: 14.0061 - val_accuracy: 0.3156
Epoch 8034/10000
1/1 [==============================] - 0s 115ms/step - loss: 4.5941e-06 - accuracy: 1.0000 - val_loss: 14.0061 - val_accuracy: 0.3157
Epoch 8035/10000
1/1 [==============================] - 0s 103ms/step - loss: 4.5919e-06 - accuracy: 1.0000 - val_loss: 14.0070 - val_accuracy: 0.3157
Epoch 8036/10000
1/1 [==============================] - 0s 104ms/step - loss: 4.5869e-06 - accuracy: 1.0000 - val_loss: 14.0085 - val_accuracy: 0.3156
Epoch 8037/10000
1/1 [==============================] - 0s 102ms/step - loss: 4.5857e-06 - accuracy: 1.0000 - val_loss: 14.0093 - val_accuracy: 0.3155
Epoch 8038/10000
1/1 [==============================] - 0s 103ms/step - loss: 4.5812e-06 - accuracy: 1.0000 - val_loss: 14.0088 - val_accuracy: 0.3156
Epoch 8039/10000
1/1 [==============================] - 0s 102ms/step - loss: 4.5798e-06 - accuracy: 1.0000 - val_loss: 14.0088 - val_accuracy: 0.3158
Epoch 8040/10000
1/1 [==============================] - 0s 111ms/step - loss: 4.5790e-06 - accuracy: 1.0000 - val_loss: 14.0093 - val_accuracy: 0.3157
Epoch 8041/10000
1/1 [==============================] - 0s 102ms/step - loss: 4.5764e-06 - accuracy: 1.0000 - val_loss: 14.0105 - val_accuracy: 0.3156
Epoch 8042/10000
1/1 [==============================] - 0s 106ms/step - loss: 4.5721e-06 - accuracy: 1.0000 - val_loss: 14.0118 - val_accuracy: 0.3154
Epoch 8043/10000
1/1 [==============================] - 0s 104ms/step - loss: 4.5712e-06 - accuracy: 1.0000 - val_loss: 14.0125 - val_accuracy: 0.3157
Epoch 8044/10000
1/1 [==============================] - 0s 113ms/step - loss: 4.5657e-06 - accuracy: 1.0000 - val_loss: 14.0127 - val_accuracy: 0.3157
Epoch 8045/10000
1/1 [==============================] - 0s 106ms/step - loss: 4.5621e-06 - accuracy: 1.0000 - val_loss: 14.0132 - val_accuracy: 0.3156
Epoch 8046/10000
1/1 [==============================] - 0s 110ms/step - loss: 4.5612e-06 - accuracy: 1.0000 - val_loss: 14.0136 - val_accuracy: 0.3155
Epoch 8047/10000
1/1 [==============================] - 0s 102ms/step - loss: 4.5592e-06 - accuracy: 1.0000 - val_loss: 14.0138 - val_accuracy: 0.3156
Epoch 8048/10000
1/1 [==============================] - 0s 104ms/step - loss: 4.5557e-06 - accuracy: 1.0000 - val_loss: 14.0145 - val_accuracy: 0.3157
Epoch 8049/10000
1/1 [==============================] - 0s 107ms/step - loss: 4.5535e-06 - accuracy: 1.0000 - val_loss: 14.0155 - val_accuracy: 0.3156
Epoch 8050/10000
1/1 [==============================] - 0s 104ms/step - loss: 4.5516e-06 - accuracy: 1.0000 - val_loss: 14.0158 - val_accuracy: 0.3156
Epoch 8051/10000
1/1 [==============================] - 0s 103ms/step - loss: 4.5488e-06 - accuracy: 1.0000 - val_loss: 14.0162 - val_accuracy: 0.3157
Epoch 8052/10000
1/1 [==============================] - 0s 105ms/step - loss: 4.5476e-06 - accuracy: 1.0000 - val_loss: 14.0167 - val_accuracy: 0.3157
Epoch 8053/10000
1/1 [==============================] - 0s 106ms/step - loss: 4.5459e-06 - accuracy: 1.0000 - val_loss: 14.0175 - val_accuracy: 0.3157
Epoch 8054/10000
1/1 [==============================] - 0s 103ms/step - loss: 4.5423e-06 - accuracy: 1.0000 - val_loss: 14.0191 - val_accuracy: 0.3156
Epoch 8055/10000
1/1 [==============================] - 0s 103ms/step - loss: 4.5380e-06 - accuracy: 1.0000 - val_loss: 14.0199 - val_accuracy: 0.3157
Epoch 8056/10000
1/1 [==============================] - 0s 104ms/step - loss: 4.5354e-06 - accuracy: 1.0000 - val_loss: 14.0197 - val_accuracy: 0.3156
Epoch 8057/10000
1/1 [==============================] - 0s 105ms/step - loss: 4.5321e-06 - accuracy: 1.0000 - val_loss: 14.0197 - val_accuracy: 0.3157
Epoch 8058/10000
1/1 [==============================] - 0s 102ms/step - loss: 4.5314e-06 - accuracy: 1.0000 - val_loss: 14.0200 - val_accuracy: 0.3157
Epoch 8059/10000
1/1 [==============================] - 0s 110ms/step - loss: 4.5292e-06 - accuracy: 1.0000 - val_loss: 14.0207 - val_accuracy: 0.3157
Epoch 8060/10000
1/1 [==============================] - 0s 106ms/step - loss: 4.5275e-06 - accuracy: 1.0000 - val_loss: 14.0217 - val_accuracy: 0.3156
Epoch 8061/10000
1/1 [==============================] - 0s 99ms/step - loss: 4.5247e-06 - accuracy: 1.0000 - val_loss: 14.0227 - val_accuracy: 0.3156
Epoch 8062/10000
1/1 [==============================] - 0s 103ms/step - loss: 4.5209e-06 - accuracy: 1.0000 - val_loss: 14.0235 - val_accuracy: 0.3157
Epoch 8063/10000
1/1 [==============================] - 0s 107ms/step - loss: 4.5218e-06 - accuracy: 1.0000 - val_loss: 14.0240 - val_accuracy: 0.3157
Epoch 8064/10000
1/1 [==============================] - 0s 106ms/step - loss: 4.5178e-06 - accuracy: 1.0000 - val_loss: 14.0245 - val_accuracy: 0.3156
Epoch 8065/10000
1/1 [==============================] - 0s 100ms/step - loss: 4.5125e-06 - accuracy: 1.0000 - val_loss: 14.0245 - val_accuracy: 0.3157
Epoch 8066/10000
1/1 [==============================] - 0s 101ms/step - loss: 4.5099e-06 - accuracy: 1.0000 - val_loss: 14.0246 - val_accuracy: 0.3157
Epoch 8067/10000
1/1 [==============================] - 0s 106ms/step - loss: 4.5097e-06 - accuracy: 1.0000 - val_loss: 14.0259 - val_accuracy: 0.3157
Epoch 8068/10000
1/1 [==============================] - 0s 102ms/step - loss: 4.5070e-06 - accuracy: 1.0000 - val_loss: 14.0278 - val_accuracy: 0.3155
Epoch 8069/10000
1/1 [==============================] - 0s 109ms/step - loss: 4.5020e-06 - accuracy: 1.0000 - val_loss: 14.0284 - val_accuracy: 0.3157
Epoch 8070/10000
1/1 [==============================] - 0s 102ms/step - loss: 4.5004e-06 - accuracy: 1.0000 - val_loss: 14.0274 - val_accuracy: 0.3158
Epoch 8071/10000
1/1 [==============================] - 0s 102ms/step - loss: 4.4975e-06 - accuracy: 1.0000 - val_loss: 14.0271 - val_accuracy: 0.3157
Epoch 8072/10000
1/1 [==============================] - 0s 117ms/step - loss: 4.4970e-06 - accuracy: 1.0000 - val_loss: 14.0278 - val_accuracy: 0.3157
Epoch 8073/10000
1/1 [==============================] - 0s 105ms/step - loss: 4.4932e-06 - accuracy: 1.0000 - val_loss: 14.0288 - val_accuracy: 0.3157
Epoch 8074/10000
1/1 [==============================] - 0s 104ms/step - loss: 4.4913e-06 - accuracy: 1.0000 - val_loss: 14.0297 - val_accuracy: 0.3156
Epoch 8075/10000
1/1 [==============================] - 0s 105ms/step - loss: 4.4880e-06 - accuracy: 1.0000 - val_loss: 14.0310 - val_accuracy: 0.3157
Epoch 8076/10000
1/1 [==============================] - 0s 105ms/step - loss: 4.4830e-06 - accuracy: 1.0000 - val_loss: 14.0325 - val_accuracy: 0.3157
Epoch 8077/10000
1/1 [==============================] - 0s 113ms/step - loss: 4.4825e-06 - accuracy: 1.0000 - val_loss: 14.0328 - val_accuracy: 0.3156
Epoch 8078/10000
1/1 [==============================] - 0s 103ms/step - loss: 4.4796e-06 - accuracy: 1.0000 - val_loss: 14.0326 - val_accuracy: 0.3157
Epoch 8079/10000
1/1 [==============================] - 0s 105ms/step - loss: 4.4756e-06 - accuracy: 1.0000 - val_loss: 14.0327 - val_accuracy: 0.3156
Epoch 8080/10000
1/1 [==============================] - 0s 100ms/step - loss: 4.4744e-06 - accuracy: 1.0000 - val_loss: 14.0329 - val_accuracy: 0.3157
Epoch 8081/10000
1/1 [==============================] - 0s 102ms/step - loss: 4.4708e-06 - accuracy: 1.0000 - val_loss: 14.0338 - val_accuracy: 0.3158
Epoch 8082/10000
1/1 [==============================] - 0s 101ms/step - loss: 4.4672e-06 - accuracy: 1.0000 - val_loss: 14.0349 - val_accuracy: 0.3159
Epoch 8083/10000
1/1 [==============================] - 0s 101ms/step - loss: 4.4658e-06 - accuracy: 1.0000 - val_loss: 14.0357 - val_accuracy: 0.3158
Epoch 8084/10000
1/1 [==============================] - 0s 104ms/step - loss: 4.4627e-06 - accuracy: 1.0000 - val_loss: 14.0358 - val_accuracy: 0.3158
Epoch 8085/10000
1/1 [==============================] - 0s 103ms/step - loss: 4.4584e-06 - accuracy: 1.0000 - val_loss: 14.0366 - val_accuracy: 0.3156
Epoch 8086/10000
1/1 [==============================] - 0s 107ms/step - loss: 4.4563e-06 - accuracy: 1.0000 - val_loss: 14.0378 - val_accuracy: 0.3156
Epoch 8087/10000
1/1 [==============================] - 0s 104ms/step - loss: 4.4563e-06 - accuracy: 1.0000 - val_loss: 14.0386 - val_accuracy: 0.3156
Epoch 8088/10000
1/1 [==============================] - 0s 101ms/step - loss: 4.4527e-06 - accuracy: 1.0000 - val_loss: 14.0388 - val_accuracy: 0.3156
Epoch 8089/10000
1/1 [==============================] - 0s 108ms/step - loss: 4.4484e-06 - accuracy: 1.0000 - val_loss: 14.0391 - val_accuracy: 0.3157
Epoch 8090/10000
1/1 [==============================] - 0s 108ms/step - loss: 4.4472e-06 - accuracy: 1.0000 - val_loss: 14.0395 - val_accuracy: 0.3158
Epoch 8091/10000
1/1 [==============================] - 0s 104ms/step - loss: 4.4417e-06 - accuracy: 1.0000 - val_loss: 14.0400 - val_accuracy: 0.3158
Epoch 8092/10000
1/1 [==============================] - 0s 102ms/step - loss: 4.4419e-06 - accuracy: 1.0000 - val_loss: 14.0402 - val_accuracy: 0.3158
Epoch 8093/10000
1/1 [==============================] - 0s 101ms/step - loss: 4.4396e-06 - accuracy: 1.0000 - val_loss: 14.0410 - val_accuracy: 0.3158
Epoch 8094/10000
1/1 [==============================] - 0s 106ms/step - loss: 4.4367e-06 - accuracy: 1.0000 - val_loss: 14.0423 - val_accuracy: 0.3158
Epoch 8095/10000
1/1 [==============================] - 0s 109ms/step - loss: 4.4322e-06 - accuracy: 1.0000 - val_loss: 14.0433 - val_accuracy: 0.3158
Epoch 8096/10000
1/1 [==============================] - 0s 104ms/step - loss: 4.4315e-06 - accuracy: 1.0000 - val_loss: 14.0434 - val_accuracy: 0.3157
Epoch 8097/10000
1/1 [==============================] - 0s 105ms/step - loss: 4.4291e-06 - accuracy: 1.0000 - val_loss: 14.0437 - val_accuracy: 0.3157
Epoch 8098/10000
1/1 [==============================] - 0s 100ms/step - loss: 4.4255e-06 - accuracy: 1.0000 - val_loss: 14.0445 - val_accuracy: 0.3157
Epoch 8099/10000
1/1 [==============================] - 0s 101ms/step - loss: 4.4226e-06 - accuracy: 1.0000 - val_loss: 14.0454 - val_accuracy: 0.3157
Epoch 8100/10000
1/1 [==============================] - 0s 100ms/step - loss: 4.4198e-06 - accuracy: 1.0000 - val_loss: 14.0460 - val_accuracy: 0.3157
Epoch 8101/10000
1/1 [==============================] - 0s 107ms/step - loss: 4.4150e-06 - accuracy: 1.0000 - val_loss: 14.0464 - val_accuracy: 0.3158
Epoch 8102/10000
1/1 [==============================] - 0s 100ms/step - loss: 4.4162e-06 - accuracy: 1.0000 - val_loss: 14.0465 - val_accuracy: 0.3157
Epoch 8103/10000
1/1 [==============================] - 0s 101ms/step - loss: 4.4121e-06 - accuracy: 1.0000 - val_loss: 14.0470 - val_accuracy: 0.3158
Epoch 8104/10000
1/1 [==============================] - 0s 101ms/step - loss: 4.4112e-06 - accuracy: 1.0000 - val_loss: 14.0475 - val_accuracy: 0.3157
Epoch 8105/10000
1/1 [==============================] - 0s 104ms/step - loss: 4.4079e-06 - accuracy: 1.0000 - val_loss: 14.0482 - val_accuracy: 0.3157
Epoch 8106/10000
1/1 [==============================] - 0s 107ms/step - loss: 4.4052e-06 - accuracy: 1.0000 - val_loss: 14.0487 - val_accuracy: 0.3156
Epoch 8107/10000
1/1 [==============================] - 0s 102ms/step - loss: 4.4014e-06 - accuracy: 1.0000 - val_loss: 14.0499 - val_accuracy: 0.3156
Epoch 8108/10000
1/1 [==============================] - 0s 101ms/step - loss: 4.4026e-06 - accuracy: 1.0000 - val_loss: 14.0508 - val_accuracy: 0.3157
Epoch 8109/10000
1/1 [==============================] - 0s 101ms/step - loss: 4.3966e-06 - accuracy: 1.0000 - val_loss: 14.0511 - val_accuracy: 0.3157
Epoch 8110/10000
1/1 [==============================] - 0s 106ms/step - loss: 4.3938e-06 - accuracy: 1.0000 - val_loss: 14.0510 - val_accuracy: 0.3158
Epoch 8111/10000
1/1 [==============================] - 0s 106ms/step - loss: 4.3928e-06 - accuracy: 1.0000 - val_loss: 14.0513 - val_accuracy: 0.3158
Epoch 8112/10000
1/1 [==============================] - 0s 105ms/step - loss: 4.3893e-06 - accuracy: 1.0000 - val_loss: 14.0524 - val_accuracy: 0.3158
Epoch 8113/10000
1/1 [==============================] - 0s 105ms/step - loss: 4.3850e-06 - accuracy: 1.0000 - val_loss: 14.0534 - val_accuracy: 0.3157
Epoch 8114/10000
1/1 [==============================] - 0s 104ms/step - loss: 4.3826e-06 - accuracy: 1.0000 - val_loss: 14.0540 - val_accuracy: 0.3157
Epoch 8115/10000
1/1 [==============================] - 0s 108ms/step - loss: 4.3804e-06 - accuracy: 1.0000 - val_loss: 14.0543 - val_accuracy: 0.3157
Epoch 8116/10000
1/1 [==============================] - 0s 106ms/step - loss: 4.3792e-06 - accuracy: 1.0000 - val_loss: 14.0544 - val_accuracy: 0.3158
Epoch 8117/10000
1/1 [==============================] - 0s 116ms/step - loss: 4.3766e-06 - accuracy: 1.0000 - val_loss: 14.0548 - val_accuracy: 0.3157
Epoch 8118/10000
1/1 [==============================] - 0s 110ms/step - loss: 4.3750e-06 - accuracy: 1.0000 - val_loss: 14.0561 - val_accuracy: 0.3158
Epoch 8119/10000
1/1 [==============================] - 0s 110ms/step - loss: 4.3711e-06 - accuracy: 1.0000 - val_loss: 14.0572 - val_accuracy: 0.3156
Epoch 8120/10000
1/1 [==============================] - 0s 105ms/step - loss: 4.3673e-06 - accuracy: 1.0000 - val_loss: 14.0573 - val_accuracy: 0.3157
Epoch 8121/10000
1/1 [==============================] - 0s 104ms/step - loss: 4.3621e-06 - accuracy: 1.0000 - val_loss: 14.0569 - val_accuracy: 0.3156
Epoch 8122/10000
1/1 [==============================] - 0s 110ms/step - loss: 4.3626e-06 - accuracy: 1.0000 - val_loss: 14.0571 - val_accuracy: 0.3157
Epoch 8123/10000
1/1 [==============================] - 0s 102ms/step - loss: 4.3585e-06 - accuracy: 1.0000 - val_loss: 14.0583 - val_accuracy: 0.3157
Epoch 8124/10000
1/1 [==============================] - 0s 103ms/step - loss: 4.3578e-06 - accuracy: 1.0000 - val_loss: 14.0595 - val_accuracy: 0.3158
Epoch 8125/10000
1/1 [==============================] - 0s 109ms/step - loss: 4.3544e-06 - accuracy: 1.0000 - val_loss: 14.0607 - val_accuracy: 0.3157
Epoch 8126/10000
1/1 [==============================] - 0s 112ms/step - loss: 4.3478e-06 - accuracy: 1.0000 - val_loss: 14.0616 - val_accuracy: 0.3158
Epoch 8127/10000
1/1 [==============================] - 0s 102ms/step - loss: 4.3468e-06 - accuracy: 1.0000 - val_loss: 14.0620 - val_accuracy: 0.3158
Epoch 8128/10000
1/1 [==============================] - 0s 101ms/step - loss: 4.3444e-06 - accuracy: 1.0000 - val_loss: 14.0616 - val_accuracy: 0.3156
Epoch 8129/10000
1/1 [==============================] - 0s 112ms/step - loss: 4.3421e-06 - accuracy: 1.0000 - val_loss: 14.0618 - val_accuracy: 0.3156
Epoch 8130/10000
1/1 [==============================] - 0s 104ms/step - loss: 4.3397e-06 - accuracy: 1.0000 - val_loss: 14.0629 - val_accuracy: 0.3159
Epoch 8131/10000
1/1 [==============================] - 0s 103ms/step - loss: 4.3373e-06 - accuracy: 1.0000 - val_loss: 14.0640 - val_accuracy: 0.3159
Epoch 8132/10000
1/1 [==============================] - 0s 106ms/step - loss: 4.3325e-06 - accuracy: 1.0000 - val_loss: 14.0647 - val_accuracy: 0.3156
Epoch 8133/10000
1/1 [==============================] - 0s 115ms/step - loss: 4.3304e-06 - accuracy: 1.0000 - val_loss: 14.0655 - val_accuracy: 0.3157
Epoch 8134/10000
1/1 [==============================] - 0s 109ms/step - loss: 4.3275e-06 - accuracy: 1.0000 - val_loss: 14.0659 - val_accuracy: 0.3156
Epoch 8135/10000
1/1 [==============================] - 0s 103ms/step - loss: 4.3261e-06 - accuracy: 1.0000 - val_loss: 14.0660 - val_accuracy: 0.3155
Epoch 8136/10000
1/1 [==============================] - 0s 106ms/step - loss: 4.3213e-06 - accuracy: 1.0000 - val_loss: 14.0666 - val_accuracy: 0.3157
Epoch 8137/10000
1/1 [==============================] - 0s 103ms/step - loss: 4.3225e-06 - accuracy: 1.0000 - val_loss: 14.0673 - val_accuracy: 0.3160
Epoch 8138/10000
1/1 [==============================] - 0s 105ms/step - loss: 4.3204e-06 - accuracy: 1.0000 - val_loss: 14.0681 - val_accuracy: 0.3160
Epoch 8139/10000
1/1 [==============================] - 0s 109ms/step - loss: 4.3175e-06 - accuracy: 1.0000 - val_loss: 14.0689 - val_accuracy: 0.3158
Epoch 8140/10000
1/1 [==============================] - 0s 102ms/step - loss: 4.3144e-06 - accuracy: 1.0000 - val_loss: 14.0695 - val_accuracy: 0.3158
Epoch 8141/10000
1/1 [==============================] - 0s 103ms/step - loss: 4.3115e-06 - accuracy: 1.0000 - val_loss: 14.0694 - val_accuracy: 0.3156
Epoch 8142/10000
1/1 [==============================] - 0s 103ms/step - loss: 4.3103e-06 - accuracy: 1.0000 - val_loss: 14.0700 - val_accuracy: 0.3155
Epoch 8143/10000
1/1 [==============================] - 0s 99ms/step - loss: 4.3063e-06 - accuracy: 1.0000 - val_loss: 14.0713 - val_accuracy: 0.3159
Epoch 8144/10000
1/1 [==============================] - 0s 103ms/step - loss: 4.3039e-06 - accuracy: 1.0000 - val_loss: 14.0713 - val_accuracy: 0.3157
Epoch 8145/10000
1/1 [==============================] - 0s 103ms/step - loss: 4.3025e-06 - accuracy: 1.0000 - val_loss: 14.0708 - val_accuracy: 0.3157
Epoch 8146/10000
1/1 [==============================] - 0s 105ms/step - loss: 4.2996e-06 - accuracy: 1.0000 - val_loss: 14.0712 - val_accuracy: 0.3155
Epoch 8147/10000
1/1 [==============================] - 0s 103ms/step - loss: 4.2977e-06 - accuracy: 1.0000 - val_loss: 14.0728 - val_accuracy: 0.3156
Epoch 8148/10000
1/1 [==============================] - 0s 107ms/step - loss: 4.2948e-06 - accuracy: 1.0000 - val_loss: 14.0748 - val_accuracy: 0.3157
Epoch 8149/10000
1/1 [==============================] - 0s 102ms/step - loss: 4.2920e-06 - accuracy: 1.0000 - val_loss: 14.0755 - val_accuracy: 0.3156
Epoch 8150/10000
1/1 [==============================] - 0s 104ms/step - loss: 4.2891e-06 - accuracy: 1.0000 - val_loss: 14.0747 - val_accuracy: 0.3156
Epoch 8151/10000
1/1 [==============================] - 0s 109ms/step - loss: 4.2836e-06 - accuracy: 1.0000 - val_loss: 14.0748 - val_accuracy: 0.3157
Epoch 8152/10000
1/1 [==============================] - 0s 112ms/step - loss: 4.2858e-06 - accuracy: 1.0000 - val_loss: 14.0754 - val_accuracy: 0.3158
Epoch 8153/10000
1/1 [==============================] - 0s 105ms/step - loss: 4.2789e-06 - accuracy: 1.0000 - val_loss: 14.0760 - val_accuracy: 0.3158
Epoch 8154/10000
1/1 [==============================] - 0s 105ms/step - loss: 4.2770e-06 - accuracy: 1.0000 - val_loss: 14.0768 - val_accuracy: 0.3158
Epoch 8155/10000
1/1 [==============================] - 0s 105ms/step - loss: 4.2760e-06 - accuracy: 1.0000 - val_loss: 14.0780 - val_accuracy: 0.3158
Epoch 8156/10000
1/1 [==============================] - 0s 109ms/step - loss: 4.2722e-06 - accuracy: 1.0000 - val_loss: 14.0790 - val_accuracy: 0.3158
Epoch 8157/10000
1/1 [==============================] - 0s 105ms/step - loss: 4.2693e-06 - accuracy: 1.0000 - val_loss: 14.0792 - val_accuracy: 0.3156
Epoch 8158/10000
1/1 [==============================] - 0s 104ms/step - loss: 4.2658e-06 - accuracy: 1.0000 - val_loss: 14.0794 - val_accuracy: 0.3158
Epoch 8159/10000
1/1 [==============================] - 0s 102ms/step - loss: 4.2660e-06 - accuracy: 1.0000 - val_loss: 14.0798 - val_accuracy: 0.3156
Epoch 8160/10000
1/1 [==============================] - 0s 103ms/step - loss: 4.2600e-06 - accuracy: 1.0000 - val_loss: 14.0805 - val_accuracy: 0.3158
Epoch 8161/10000
1/1 [==============================] - 0s 104ms/step - loss: 4.2605e-06 - accuracy: 1.0000 - val_loss: 14.0814 - val_accuracy: 0.3158
Epoch 8162/10000
1/1 [==============================] - 0s 101ms/step - loss: 4.2553e-06 - accuracy: 1.0000 - val_loss: 14.0824 - val_accuracy: 0.3157
Epoch 8163/10000
1/1 [==============================] - 0s 103ms/step - loss: 4.2579e-06 - accuracy: 1.0000 - val_loss: 14.0829 - val_accuracy: 0.3158
Epoch 8164/10000
1/1 [==============================] - 0s 103ms/step - loss: 4.2534e-06 - accuracy: 1.0000 - val_loss: 14.0829 - val_accuracy: 0.3157
Epoch 8165/10000
1/1 [==============================] - 0s 108ms/step - loss: 4.2493e-06 - accuracy: 1.0000 - val_loss: 14.0829 - val_accuracy: 0.3157
Epoch 8166/10000
1/1 [==============================] - 0s 114ms/step - loss: 4.2474e-06 - accuracy: 1.0000 - val_loss: 14.0835 - val_accuracy: 0.3157
Epoch 8167/10000
1/1 [==============================] - 0s 104ms/step - loss: 4.2460e-06 - accuracy: 1.0000 - val_loss: 14.0850 - val_accuracy: 0.3160
Epoch 8168/10000
1/1 [==============================] - 0s 107ms/step - loss: 4.2414e-06 - accuracy: 1.0000 - val_loss: 14.0867 - val_accuracy: 0.3158
Epoch 8169/10000
1/1 [==============================] - 0s 106ms/step - loss: 4.2388e-06 - accuracy: 1.0000 - val_loss: 14.0860 - val_accuracy: 0.3156
Epoch 8170/10000
1/1 [==============================] - 0s 102ms/step - loss: 4.2357e-06 - accuracy: 1.0000 - val_loss: 14.0857 - val_accuracy: 0.3156
Epoch 8171/10000
1/1 [==============================] - 0s 105ms/step - loss: 4.2345e-06 - accuracy: 1.0000 - val_loss: 14.0864 - val_accuracy: 0.3157
Epoch 8172/10000
1/1 [==============================] - 0s 100ms/step - loss: 4.2307e-06 - accuracy: 1.0000 - val_loss: 14.0878 - val_accuracy: 0.3158
Epoch 8173/10000
1/1 [==============================] - 0s 103ms/step - loss: 4.2295e-06 - accuracy: 1.0000 - val_loss: 14.0887 - val_accuracy: 0.3158
Epoch 8174/10000
1/1 [==============================] - 0s 103ms/step - loss: 4.2255e-06 - accuracy: 1.0000 - val_loss: 14.0892 - val_accuracy: 0.3157
Epoch 8175/10000
1/1 [==============================] - 0s 107ms/step - loss: 4.2250e-06 - accuracy: 1.0000 - val_loss: 14.0900 - val_accuracy: 0.3157
Epoch 8176/10000
1/1 [==============================] - 0s 101ms/step - loss: 4.2219e-06 - accuracy: 1.0000 - val_loss: 14.0904 - val_accuracy: 0.3157
Epoch 8177/10000
1/1 [==============================] - 0s 122ms/step - loss: 4.2209e-06 - accuracy: 1.0000 - val_loss: 14.0905 - val_accuracy: 0.3157
Epoch 8178/10000
1/1 [==============================] - 0s 113ms/step - loss: 4.2166e-06 - accuracy: 1.0000 - val_loss: 14.0907 - val_accuracy: 0.3157
Epoch 8179/10000
1/1 [==============================] - 0s 107ms/step - loss: 4.2133e-06 - accuracy: 1.0000 - val_loss: 14.0918 - val_accuracy: 0.3155
Epoch 8180/10000
1/1 [==============================] - 0s 111ms/step - loss: 4.2114e-06 - accuracy: 1.0000 - val_loss: 14.0931 - val_accuracy: 0.3157
Epoch 8181/10000
1/1 [==============================] - 0s 102ms/step - loss: 4.2081e-06 - accuracy: 1.0000 - val_loss: 14.0938 - val_accuracy: 0.3157
Epoch 8182/10000
1/1 [==============================] - 0s 99ms/step - loss: 4.2064e-06 - accuracy: 1.0000 - val_loss: 14.0940 - val_accuracy: 0.3157
Epoch 8183/10000
1/1 [==============================] - 0s 101ms/step - loss: 4.2062e-06 - accuracy: 1.0000 - val_loss: 14.0941 - val_accuracy: 0.3157
Epoch 8184/10000
1/1 [==============================] - 0s 101ms/step - loss: 4.2009e-06 - accuracy: 1.0000 - val_loss: 14.0947 - val_accuracy: 0.3156
Epoch 8185/10000
1/1 [==============================] - 0s 109ms/step - loss: 4.2000e-06 - accuracy: 1.0000 - val_loss: 14.0956 - val_accuracy: 0.3159
Epoch 8186/10000
1/1 [==============================] - 0s 100ms/step - loss: 4.1964e-06 - accuracy: 1.0000 - val_loss: 14.0963 - val_accuracy: 0.3158
Epoch 8187/10000
1/1 [==============================] - 0s 112ms/step - loss: 4.1928e-06 - accuracy: 1.0000 - val_loss: 14.0961 - val_accuracy: 0.3157
Epoch 8188/10000
1/1 [==============================] - 0s 107ms/step - loss: 4.1907e-06 - accuracy: 1.0000 - val_loss: 14.0965 - val_accuracy: 0.3156
Epoch 8189/10000
1/1 [==============================] - 0s 104ms/step - loss: 4.1868e-06 - accuracy: 1.0000 - val_loss: 14.0972 - val_accuracy: 0.3155
Epoch 8190/10000
1/1 [==============================] - 0s 112ms/step - loss: 4.1866e-06 - accuracy: 1.0000 - val_loss: 14.0985 - val_accuracy: 0.3157
Epoch 8191/10000
1/1 [==============================] - 0s 106ms/step - loss: 4.1821e-06 - accuracy: 1.0000 - val_loss: 14.0996 - val_accuracy: 0.3156
Epoch 8192/10000
1/1 [==============================] - 0s 104ms/step - loss: 4.1797e-06 - accuracy: 1.0000 - val_loss: 14.0997 - val_accuracy: 0.3156
Epoch 8193/10000
1/1 [==============================] - 0s 100ms/step - loss: 4.1754e-06 - accuracy: 1.0000 - val_loss: 14.0999 - val_accuracy: 0.3158
Epoch 8194/10000
1/1 [==============================] - 0s 102ms/step - loss: 4.1744e-06 - accuracy: 1.0000 - val_loss: 14.1005 - val_accuracy: 0.3157
Epoch 8195/10000
1/1 [==============================] - 0s 102ms/step - loss: 4.1723e-06 - accuracy: 1.0000 - val_loss: 14.1014 - val_accuracy: 0.3157
Epoch 8196/10000
1/1 [==============================] - 0s 106ms/step - loss: 4.1666e-06 - accuracy: 1.0000 - val_loss: 14.1024 - val_accuracy: 0.3156
Epoch 8197/10000
1/1 [==============================] - 0s 101ms/step - loss: 4.1644e-06 - accuracy: 1.0000 - val_loss: 14.1032 - val_accuracy: 0.3157
Epoch 8198/10000
1/1 [==============================] - 0s 100ms/step - loss: 4.1637e-06 - accuracy: 1.0000 - val_loss: 14.1031 - val_accuracy: 0.3158
Epoch 8199/10000
1/1 [==============================] - 0s 99ms/step - loss: 4.1663e-06 - accuracy: 1.0000 - val_loss: 14.1029 - val_accuracy: 0.3158
Epoch 8200/10000
1/1 [==============================] - 0s 104ms/step - loss: 4.1630e-06 - accuracy: 1.0000 - val_loss: 14.1036 - val_accuracy: 0.3157
Epoch 8201/10000
1/1 [==============================] - 0s 102ms/step - loss: 4.1587e-06 - accuracy: 1.0000 - val_loss: 14.1055 - val_accuracy: 0.3156
Epoch 8202/10000
1/1 [==============================] - 0s 99ms/step - loss: 4.1518e-06 - accuracy: 1.0000 - val_loss: 14.1068 - val_accuracy: 0.3156
Epoch 8203/10000
1/1 [==============================] - 0s 105ms/step - loss: 4.1537e-06 - accuracy: 1.0000 - val_loss: 14.1061 - val_accuracy: 0.3159
Epoch 8204/10000
1/1 [==============================] - 0s 107ms/step - loss: 4.1477e-06 - accuracy: 1.0000 - val_loss: 14.1054 - val_accuracy: 0.3155
Epoch 8205/10000
1/1 [==============================] - 0s 100ms/step - loss: 4.1496e-06 - accuracy: 1.0000 - val_loss: 14.1061 - val_accuracy: 0.3155
Epoch 8206/10000
1/1 [==============================] - 0s 105ms/step - loss: 4.1461e-06 - accuracy: 1.0000 - val_loss: 14.1078 - val_accuracy: 0.3158
Epoch 8207/10000
1/1 [==============================] - 0s 113ms/step - loss: 4.1442e-06 - accuracy: 1.0000 - val_loss: 14.1093 - val_accuracy: 0.3156
Epoch 8208/10000
1/1 [==============================] - 0s 105ms/step - loss: 4.1411e-06 - accuracy: 1.0000 - val_loss: 14.1099 - val_accuracy: 0.3155
Epoch 8209/10000
1/1 [==============================] - 0s 104ms/step - loss: 4.1382e-06 - accuracy: 1.0000 - val_loss: 14.1093 - val_accuracy: 0.3155
Epoch 8210/10000
1/1 [==============================] - 0s 103ms/step - loss: 4.1358e-06 - accuracy: 1.0000 - val_loss: 14.1092 - val_accuracy: 0.3156
Epoch 8211/10000
1/1 [==============================] - 0s 99ms/step - loss: 4.1315e-06 - accuracy: 1.0000 - val_loss: 14.1092 - val_accuracy: 0.3157
Epoch 8212/10000
1/1 [==============================] - 0s 104ms/step - loss: 4.1306e-06 - accuracy: 1.0000 - val_loss: 14.1103 - val_accuracy: 0.3155
Epoch 8213/10000
1/1 [==============================] - 0s 104ms/step - loss: 4.1265e-06 - accuracy: 1.0000 - val_loss: 14.1120 - val_accuracy: 0.3156
Epoch 8214/10000
1/1 [==============================] - 0s 102ms/step - loss: 4.1246e-06 - accuracy: 1.0000 - val_loss: 14.1133 - val_accuracy: 0.3156
Epoch 8215/10000
1/1 [==============================] - 0s 106ms/step - loss: 4.1232e-06 - accuracy: 1.0000 - val_loss: 14.1139 - val_accuracy: 0.3155
Epoch 8216/10000
1/1 [==============================] - 0s 106ms/step - loss: 4.1213e-06 - accuracy: 1.0000 - val_loss: 14.1137 - val_accuracy: 0.3157
Epoch 8217/10000
1/1 [==============================] - 0s 100ms/step - loss: 4.1175e-06 - accuracy: 1.0000 - val_loss: 14.1137 - val_accuracy: 0.3156
Epoch 8218/10000
1/1 [==============================] - 0s 108ms/step - loss: 4.1158e-06 - accuracy: 1.0000 - val_loss: 14.1144 - val_accuracy: 0.3156
Epoch 8219/10000
1/1 [==============================] - 0s 100ms/step - loss: 4.1139e-06 - accuracy: 1.0000 - val_loss: 14.1153 - val_accuracy: 0.3157
Epoch 8220/10000
1/1 [==============================] - 0s 99ms/step - loss: 4.1120e-06 - accuracy: 1.0000 - val_loss: 14.1159 - val_accuracy: 0.3156
Epoch 8221/10000
1/1 [==============================] - 0s 100ms/step - loss: 4.1079e-06 - accuracy: 1.0000 - val_loss: 14.1169 - val_accuracy: 0.3156
Epoch 8222/10000
1/1 [==============================] - 0s 103ms/step - loss: 4.1086e-06 - accuracy: 1.0000 - val_loss: 14.1180 - val_accuracy: 0.3156
Epoch 8223/10000
1/1 [==============================] - 0s 100ms/step - loss: 4.1044e-06 - accuracy: 1.0000 - val_loss: 14.1180 - val_accuracy: 0.3156
Epoch 8224/10000
1/1 [==============================] - 0s 103ms/step - loss: 4.1015e-06 - accuracy: 1.0000 - val_loss: 14.1180 - val_accuracy: 0.3155
Epoch 8225/10000
1/1 [==============================] - 0s 107ms/step - loss: 4.0993e-06 - accuracy: 1.0000 - val_loss: 14.1188 - val_accuracy: 0.3155
Epoch 8226/10000
1/1 [==============================] - 0s 103ms/step - loss: 4.0965e-06 - accuracy: 1.0000 - val_loss: 14.1200 - val_accuracy: 0.3156
Epoch 8227/10000
1/1 [==============================] - 0s 103ms/step - loss: 4.0927e-06 - accuracy: 1.0000 - val_loss: 14.1205 - val_accuracy: 0.3155
Epoch 8228/10000
1/1 [==============================] - 0s 112ms/step - loss: 4.0922e-06 - accuracy: 1.0000 - val_loss: 14.1206 - val_accuracy: 0.3157
Epoch 8229/10000
1/1 [==============================] - 0s 105ms/step - loss: 4.0905e-06 - accuracy: 1.0000 - val_loss: 14.1214 - val_accuracy: 0.3157
Epoch 8230/10000
1/1 [==============================] - 0s 113ms/step - loss: 4.0843e-06 - accuracy: 1.0000 - val_loss: 14.1218 - val_accuracy: 0.3157
Epoch 8231/10000
1/1 [==============================] - 0s 119ms/step - loss: 4.0831e-06 - accuracy: 1.0000 - val_loss: 14.1222 - val_accuracy: 0.3156
Epoch 8232/10000
1/1 [==============================] - 0s 112ms/step - loss: 4.0812e-06 - accuracy: 1.0000 - val_loss: 14.1233 - val_accuracy: 0.3154
Epoch 8233/10000
1/1 [==============================] - 0s 113ms/step - loss: 4.0781e-06 - accuracy: 1.0000 - val_loss: 14.1240 - val_accuracy: 0.3156
Epoch 8234/10000
1/1 [==============================] - 0s 112ms/step - loss: 4.0741e-06 - accuracy: 1.0000 - val_loss: 14.1246 - val_accuracy: 0.3156
Epoch 8235/10000
1/1 [==============================] - 0s 105ms/step - loss: 4.0736e-06 - accuracy: 1.0000 - val_loss: 14.1246 - val_accuracy: 0.3157
Epoch 8236/10000
1/1 [==============================] - 0s 102ms/step - loss: 4.0707e-06 - accuracy: 1.0000 - val_loss: 14.1245 - val_accuracy: 0.3156
Epoch 8237/10000
1/1 [==============================] - 0s 103ms/step - loss: 4.0712e-06 - accuracy: 1.0000 - val_loss: 14.1253 - val_accuracy: 0.3155
Epoch 8238/10000
1/1 [==============================] - 0s 103ms/step - loss: 4.0705e-06 - accuracy: 1.0000 - val_loss: 14.1267 - val_accuracy: 0.3156
Epoch 8239/10000
1/1 [==============================] - 0s 103ms/step - loss: 4.0660e-06 - accuracy: 1.0000 - val_loss: 14.1279 - val_accuracy: 0.3154
Epoch 8240/10000
1/1 [==============================] - 0s 100ms/step - loss: 4.0638e-06 - accuracy: 1.0000 - val_loss: 14.1277 - val_accuracy: 0.3155
Epoch 8241/10000
1/1 [==============================] - 0s 106ms/step - loss: 4.0598e-06 - accuracy: 1.0000 - val_loss: 14.1275 - val_accuracy: 0.3156
Epoch 8242/10000
1/1 [==============================] - 0s 107ms/step - loss: 4.0600e-06 - accuracy: 1.0000 - val_loss: 14.1279 - val_accuracy: 0.3156
Epoch 8243/10000
1/1 [==============================] - 0s 107ms/step - loss: 4.0593e-06 - accuracy: 1.0000 - val_loss: 14.1288 - val_accuracy: 0.3155
Epoch 8244/10000
1/1 [==============================] - 0s 110ms/step - loss: 4.0540e-06 - accuracy: 1.0000 - val_loss: 14.1302 - val_accuracy: 0.3154
Epoch 8245/10000
1/1 [==============================] - 0s 109ms/step - loss: 4.0526e-06 - accuracy: 1.0000 - val_loss: 14.1316 - val_accuracy: 0.3154
Epoch 8246/10000
1/1 [==============================] - 0s 113ms/step - loss: 4.0505e-06 - accuracy: 1.0000 - val_loss: 14.1317 - val_accuracy: 0.3154
Epoch 8247/10000
1/1 [==============================] - 0s 105ms/step - loss: 4.0476e-06 - accuracy: 1.0000 - val_loss: 14.1314 - val_accuracy: 0.3155
Epoch 8248/10000
1/1 [==============================] - 0s 108ms/step - loss: 4.0438e-06 - accuracy: 1.0000 - val_loss: 14.1318 - val_accuracy: 0.3155
Epoch 8249/10000
1/1 [==============================] - 0s 109ms/step - loss: 4.0397e-06 - accuracy: 1.0000 - val_loss: 14.1332 - val_accuracy: 0.3153
Epoch 8250/10000
1/1 [==============================] - 0s 103ms/step - loss: 4.0428e-06 - accuracy: 1.0000 - val_loss: 14.1342 - val_accuracy: 0.3153
Epoch 8251/10000
1/1 [==============================] - 0s 102ms/step - loss: 4.0390e-06 - accuracy: 1.0000 - val_loss: 14.1341 - val_accuracy: 0.3155
Epoch 8252/10000
1/1 [==============================] - 0s 105ms/step - loss: 4.0343e-06 - accuracy: 1.0000 - val_loss: 14.1346 - val_accuracy: 0.3156
Epoch 8253/10000
1/1 [==============================] - 0s 105ms/step - loss: 4.0314e-06 - accuracy: 1.0000 - val_loss: 14.1357 - val_accuracy: 0.3155
Epoch 8254/10000
1/1 [==============================] - 0s 106ms/step - loss: 4.0319e-06 - accuracy: 1.0000 - val_loss: 14.1366 - val_accuracy: 0.3154
Epoch 8255/10000
1/1 [==============================] - 0s 110ms/step - loss: 4.0283e-06 - accuracy: 1.0000 - val_loss: 14.1366 - val_accuracy: 0.3153
Epoch 8256/10000
1/1 [==============================] - 0s 101ms/step - loss: 4.0269e-06 - accuracy: 1.0000 - val_loss: 14.1366 - val_accuracy: 0.3154
Epoch 8257/10000
1/1 [==============================] - 0s 99ms/step - loss: 4.0202e-06 - accuracy: 1.0000 - val_loss: 14.1367 - val_accuracy: 0.3154
Epoch 8258/10000
1/1 [==============================] - 0s 111ms/step - loss: 4.0219e-06 - accuracy: 1.0000 - val_loss: 14.1380 - val_accuracy: 0.3154
Epoch 8259/10000
1/1 [==============================] - 0s 101ms/step - loss: 4.0192e-06 - accuracy: 1.0000 - val_loss: 14.1387 - val_accuracy: 0.3154
Epoch 8260/10000
1/1 [==============================] - 0s 106ms/step - loss: 4.0178e-06 - accuracy: 1.0000 - val_loss: 14.1389 - val_accuracy: 0.3155
Epoch 8261/10000
1/1 [==============================] - 0s 104ms/step - loss: 4.0138e-06 - accuracy: 1.0000 - val_loss: 14.1394 - val_accuracy: 0.3154
Epoch 8262/10000
1/1 [==============================] - 0s 106ms/step - loss: 4.0102e-06 - accuracy: 1.0000 - val_loss: 14.1409 - val_accuracy: 0.3153
Epoch 8263/10000
1/1 [==============================] - 0s 107ms/step - loss: 4.0083e-06 - accuracy: 1.0000 - val_loss: 14.1420 - val_accuracy: 0.3153
Epoch 8264/10000
1/1 [==============================] - 0s 98ms/step - loss: 4.0064e-06 - accuracy: 1.0000 - val_loss: 14.1426 - val_accuracy: 0.3153
Epoch 8265/10000
1/1 [==============================] - 0s 105ms/step - loss: 4.0042e-06 - accuracy: 1.0000 - val_loss: 14.1426 - val_accuracy: 0.3153
Epoch 8266/10000
1/1 [==============================] - 0s 98ms/step - loss: 4.0018e-06 - accuracy: 1.0000 - val_loss: 14.1428 - val_accuracy: 0.3155
Epoch 8267/10000
1/1 [==============================] - 0s 108ms/step - loss: 3.9987e-06 - accuracy: 1.0000 - val_loss: 14.1437 - val_accuracy: 0.3154
Epoch 8268/10000
1/1 [==============================] - 0s 109ms/step - loss: 3.9973e-06 - accuracy: 1.0000 - val_loss: 14.1448 - val_accuracy: 0.3154
Epoch 8269/10000
1/1 [==============================] - 0s 101ms/step - loss: 3.9959e-06 - accuracy: 1.0000 - val_loss: 14.1450 - val_accuracy: 0.3153
Epoch 8270/10000
1/1 [==============================] - 0s 111ms/step - loss: 3.9901e-06 - accuracy: 1.0000 - val_loss: 14.1452 - val_accuracy: 0.3154
Epoch 8271/10000
1/1 [==============================] - 0s 106ms/step - loss: 3.9885e-06 - accuracy: 1.0000 - val_loss: 14.1454 - val_accuracy: 0.3154
Epoch 8272/10000
1/1 [==============================] - 0s 109ms/step - loss: 3.9849e-06 - accuracy: 1.0000 - val_loss: 14.1463 - val_accuracy: 0.3153
Epoch 8273/10000
1/1 [==============================] - 0s 103ms/step - loss: 3.9835e-06 - accuracy: 1.0000 - val_loss: 14.1469 - val_accuracy: 0.3152
Epoch 8274/10000
1/1 [==============================] - 0s 109ms/step - loss: 3.9804e-06 - accuracy: 1.0000 - val_loss: 14.1475 - val_accuracy: 0.3153
Epoch 8275/10000
1/1 [==============================] - 0s 105ms/step - loss: 3.9801e-06 - accuracy: 1.0000 - val_loss: 14.1487 - val_accuracy: 0.3153
Epoch 8276/10000
1/1 [==============================] - 0s 107ms/step - loss: 3.9801e-06 - accuracy: 1.0000 - val_loss: 14.1493 - val_accuracy: 0.3154
Epoch 8277/10000
1/1 [==============================] - 0s 108ms/step - loss: 3.9739e-06 - accuracy: 1.0000 - val_loss: 14.1497 - val_accuracy: 0.3154
Epoch 8278/10000
1/1 [==============================] - 0s 101ms/step - loss: 3.9713e-06 - accuracy: 1.0000 - val_loss: 14.1492 - val_accuracy: 0.3154
Epoch 8279/10000
1/1 [==============================] - 0s 101ms/step - loss: 3.9689e-06 - accuracy: 1.0000 - val_loss: 14.1495 - val_accuracy: 0.3154
Epoch 8280/10000
1/1 [==============================] - 0s 109ms/step - loss: 3.9687e-06 - accuracy: 1.0000 - val_loss: 14.1509 - val_accuracy: 0.3152
Epoch 8281/10000
1/1 [==============================] - 0s 101ms/step - loss: 3.9656e-06 - accuracy: 1.0000 - val_loss: 14.1523 - val_accuracy: 0.3152
Epoch 8282/10000
1/1 [==============================] - 0s 104ms/step - loss: 3.9632e-06 - accuracy: 1.0000 - val_loss: 14.1531 - val_accuracy: 0.3153
Epoch 8283/10000
1/1 [==============================] - 0s 104ms/step - loss: 3.9625e-06 - accuracy: 1.0000 - val_loss: 14.1534 - val_accuracy: 0.3153
Epoch 8284/10000
1/1 [==============================] - 0s 99ms/step - loss: 3.9599e-06 - accuracy: 1.0000 - val_loss: 14.1537 - val_accuracy: 0.3154
Epoch 8285/10000
1/1 [==============================] - 0s 102ms/step - loss: 3.9568e-06 - accuracy: 1.0000 - val_loss: 14.1543 - val_accuracy: 0.3154
Epoch 8286/10000
1/1 [==============================] - 0s 99ms/step - loss: 3.9544e-06 - accuracy: 1.0000 - val_loss: 14.1550 - val_accuracy: 0.3153
Epoch 8287/10000
1/1 [==============================] - 0s 100ms/step - loss: 3.9532e-06 - accuracy: 1.0000 - val_loss: 14.1555 - val_accuracy: 0.3153
Epoch 8288/10000
1/1 [==============================] - 0s 102ms/step - loss: 3.9513e-06 - accuracy: 1.0000 - val_loss: 14.1560 - val_accuracy: 0.3152
Epoch 8289/10000
1/1 [==============================] - 0s 101ms/step - loss: 3.9463e-06 - accuracy: 1.0000 - val_loss: 14.1563 - val_accuracy: 0.3154
Epoch 8290/10000
1/1 [==============================] - 0s 102ms/step - loss: 3.9444e-06 - accuracy: 1.0000 - val_loss: 14.1568 - val_accuracy: 0.3154
Epoch 8291/10000
1/1 [==============================] - 0s 104ms/step - loss: 3.9415e-06 - accuracy: 1.0000 - val_loss: 14.1575 - val_accuracy: 0.3154
Epoch 8292/10000
1/1 [==============================] - 0s 109ms/step - loss: 3.9413e-06 - accuracy: 1.0000 - val_loss: 14.1586 - val_accuracy: 0.3153
Epoch 8293/10000
1/1 [==============================] - 0s 104ms/step - loss: 3.9379e-06 - accuracy: 1.0000 - val_loss: 14.1597 - val_accuracy: 0.3153
Epoch 8294/10000
1/1 [==============================] - 0s 103ms/step - loss: 3.9365e-06 - accuracy: 1.0000 - val_loss: 14.1602 - val_accuracy: 0.3153
Epoch 8295/10000
1/1 [==============================] - 0s 103ms/step - loss: 3.9329e-06 - accuracy: 1.0000 - val_loss: 14.1604 - val_accuracy: 0.3153
Epoch 8296/10000
1/1 [==============================] - 0s 103ms/step - loss: 3.9291e-06 - accuracy: 1.0000 - val_loss: 14.1607 - val_accuracy: 0.3154
Epoch 8297/10000
1/1 [==============================] - 0s 101ms/step - loss: 3.9286e-06 - accuracy: 1.0000 - val_loss: 14.1615 - val_accuracy: 0.3153
Epoch 8298/10000
1/1 [==============================] - 0s 104ms/step - loss: 3.9270e-06 - accuracy: 1.0000 - val_loss: 14.1614 - val_accuracy: 0.3154
Epoch 8299/10000
1/1 [==============================] - 0s 109ms/step - loss: 3.9234e-06 - accuracy: 1.0000 - val_loss: 14.1616 - val_accuracy: 0.3152
Epoch 8300/10000
1/1 [==============================] - 0s 105ms/step - loss: 3.9229e-06 - accuracy: 1.0000 - val_loss: 14.1622 - val_accuracy: 0.3153
Epoch 8301/10000
1/1 [==============================] - 0s 103ms/step - loss: 3.9215e-06 - accuracy: 1.0000 - val_loss: 14.1632 - val_accuracy: 0.3153
Epoch 8302/10000
1/1 [==============================] - 0s 108ms/step - loss: 3.9162e-06 - accuracy: 1.0000 - val_loss: 14.1643 - val_accuracy: 0.3154
Epoch 8303/10000
1/1 [==============================] - 0s 110ms/step - loss: 3.9153e-06 - accuracy: 1.0000 - val_loss: 14.1654 - val_accuracy: 0.3153
Epoch 8304/10000
1/1 [==============================] - 0s 105ms/step - loss: 3.9139e-06 - accuracy: 1.0000 - val_loss: 14.1659 - val_accuracy: 0.3154
Epoch 8305/10000
1/1 [==============================] - 0s 107ms/step - loss: 3.9110e-06 - accuracy: 1.0000 - val_loss: 14.1659 - val_accuracy: 0.3154
Epoch 8306/10000
1/1 [==============================] - 0s 101ms/step - loss: 3.9077e-06 - accuracy: 1.0000 - val_loss: 14.1658 - val_accuracy: 0.3153
Epoch 8307/10000
1/1 [==============================] - 0s 109ms/step - loss: 3.9060e-06 - accuracy: 1.0000 - val_loss: 14.1663 - val_accuracy: 0.3153
Epoch 8308/10000
1/1 [==============================] - 0s 105ms/step - loss: 3.9015e-06 - accuracy: 1.0000 - val_loss: 14.1677 - val_accuracy: 0.3153
Epoch 8309/10000
1/1 [==============================] - 0s 102ms/step - loss: 3.8998e-06 - accuracy: 1.0000 - val_loss: 14.1695 - val_accuracy: 0.3152
Epoch 8310/10000
1/1 [==============================] - 0s 102ms/step - loss: 3.8965e-06 - accuracy: 1.0000 - val_loss: 14.1696 - val_accuracy: 0.3153
Epoch 8311/10000
1/1 [==============================] - 0s 101ms/step - loss: 3.8974e-06 - accuracy: 1.0000 - val_loss: 14.1694 - val_accuracy: 0.3153
Epoch 8312/10000
1/1 [==============================] - 0s 101ms/step - loss: 3.8943e-06 - accuracy: 1.0000 - val_loss: 14.1697 - val_accuracy: 0.3154
Epoch 8313/10000
1/1 [==============================] - 0s 99ms/step - loss: 3.8912e-06 - accuracy: 1.0000 - val_loss: 14.1705 - val_accuracy: 0.3154
Epoch 8314/10000
1/1 [==============================] - 0s 101ms/step - loss: 3.8888e-06 - accuracy: 1.0000 - val_loss: 14.1710 - val_accuracy: 0.3152
Epoch 8315/10000
1/1 [==============================] - 0s 100ms/step - loss: 3.8867e-06 - accuracy: 1.0000 - val_loss: 14.1722 - val_accuracy: 0.3151
Epoch 8316/10000
1/1 [==============================] - 0s 101ms/step - loss: 3.8850e-06 - accuracy: 1.0000 - val_loss: 14.1728 - val_accuracy: 0.3152
Epoch 8317/10000
1/1 [==============================] - 0s 103ms/step - loss: 3.8821e-06 - accuracy: 1.0000 - val_loss: 14.1728 - val_accuracy: 0.3153
Epoch 8318/10000
1/1 [==============================] - 0s 104ms/step - loss: 3.8802e-06 - accuracy: 1.0000 - val_loss: 14.1730 - val_accuracy: 0.3154
Epoch 8319/10000
1/1 [==============================] - 0s 103ms/step - loss: 3.8783e-06 - accuracy: 1.0000 - val_loss: 14.1740 - val_accuracy: 0.3154
Epoch 8320/10000
1/1 [==============================] - 0s 101ms/step - loss: 3.8740e-06 - accuracy: 1.0000 - val_loss: 14.1754 - val_accuracy: 0.3152
Epoch 8321/10000
1/1 [==============================] - 0s 102ms/step - loss: 3.8717e-06 - accuracy: 1.0000 - val_loss: 14.1760 - val_accuracy: 0.3151
Epoch 8322/10000
1/1 [==============================] - 0s 108ms/step - loss: 3.8717e-06 - accuracy: 1.0000 - val_loss: 14.1760 - val_accuracy: 0.3152
Epoch 8323/10000
1/1 [==============================] - 0s 109ms/step - loss: 3.8705e-06 - accuracy: 1.0000 - val_loss: 14.1753 - val_accuracy: 0.3152
Epoch 8324/10000
1/1 [==============================] - 0s 105ms/step - loss: 3.8671e-06 - accuracy: 1.0000 - val_loss: 14.1755 - val_accuracy: 0.3152
Epoch 8325/10000
1/1 [==============================] - 0s 104ms/step - loss: 3.8655e-06 - accuracy: 1.0000 - val_loss: 14.1767 - val_accuracy: 0.3153
Epoch 8326/10000
1/1 [==============================] - 0s 104ms/step - loss: 3.8633e-06 - accuracy: 1.0000 - val_loss: 14.1778 - val_accuracy: 0.3154
Epoch 8327/10000
1/1 [==============================] - 0s 103ms/step - loss: 3.8597e-06 - accuracy: 1.0000 - val_loss: 14.1790 - val_accuracy: 0.3153
Epoch 8328/10000
1/1 [==============================] - 0s 99ms/step - loss: 3.8588e-06 - accuracy: 1.0000 - val_loss: 14.1801 - val_accuracy: 0.3152
Epoch 8329/10000
1/1 [==============================] - 0s 106ms/step - loss: 3.8564e-06 - accuracy: 1.0000 - val_loss: 14.1806 - val_accuracy: 0.3153
Epoch 8330/10000
1/1 [==============================] - 0s 108ms/step - loss: 3.8526e-06 - accuracy: 1.0000 - val_loss: 14.1806 - val_accuracy: 0.3154
Epoch 8331/10000
1/1 [==============================] - 0s 100ms/step - loss: 3.8497e-06 - accuracy: 1.0000 - val_loss: 14.1805 - val_accuracy: 0.3154
Epoch 8332/10000
1/1 [==============================] - 0s 104ms/step - loss: 3.8464e-06 - accuracy: 1.0000 - val_loss: 14.1813 - val_accuracy: 0.3154
Epoch 8333/10000
1/1 [==============================] - 0s 106ms/step - loss: 3.8459e-06 - accuracy: 1.0000 - val_loss: 14.1830 - val_accuracy: 0.3152
Epoch 8334/10000
1/1 [==============================] - 0s 106ms/step - loss: 3.8426e-06 - accuracy: 1.0000 - val_loss: 14.1841 - val_accuracy: 0.3151
Epoch 8335/10000
1/1 [==============================] - 0s 109ms/step - loss: 3.8409e-06 - accuracy: 1.0000 - val_loss: 14.1839 - val_accuracy: 0.3152
Epoch 8336/10000
1/1 [==============================] - 0s 108ms/step - loss: 3.8380e-06 - accuracy: 1.0000 - val_loss: 14.1835 - val_accuracy: 0.3154
Epoch 8337/10000
1/1 [==============================] - 0s 104ms/step - loss: 3.8378e-06 - accuracy: 1.0000 - val_loss: 14.1843 - val_accuracy: 0.3154
Epoch 8338/10000
1/1 [==============================] - 0s 102ms/step - loss: 3.8352e-06 - accuracy: 1.0000 - val_loss: 14.1858 - val_accuracy: 0.3152
Epoch 8339/10000
1/1 [==============================] - 0s 108ms/step - loss: 3.8335e-06 - accuracy: 1.0000 - val_loss: 14.1868 - val_accuracy: 0.3152
Epoch 8340/10000
1/1 [==============================] - 0s 104ms/step - loss: 3.8314e-06 - accuracy: 1.0000 - val_loss: 14.1866 - val_accuracy: 0.3151
Epoch 8341/10000
1/1 [==============================] - 0s 109ms/step - loss: 3.8256e-06 - accuracy: 1.0000 - val_loss: 14.1864 - val_accuracy: 0.3152
Epoch 8342/10000
1/1 [==============================] - 0s 115ms/step - loss: 3.8249e-06 - accuracy: 1.0000 - val_loss: 14.1871 - val_accuracy: 0.3154
Epoch 8343/10000
1/1 [==============================] - 0s 110ms/step - loss: 3.8233e-06 - accuracy: 1.0000 - val_loss: 14.1885 - val_accuracy: 0.3154
Epoch 8344/10000
1/1 [==============================] - 0s 109ms/step - loss: 3.8225e-06 - accuracy: 1.0000 - val_loss: 14.1896 - val_accuracy: 0.3152
Epoch 8345/10000
1/1 [==============================] - 0s 112ms/step - loss: 3.8190e-06 - accuracy: 1.0000 - val_loss: 14.1897 - val_accuracy: 0.3152
Epoch 8346/10000
1/1 [==============================] - 0s 122ms/step - loss: 3.8199e-06 - accuracy: 1.0000 - val_loss: 14.1892 - val_accuracy: 0.3152
Epoch 8347/10000
1/1 [==============================] - 0s 117ms/step - loss: 3.8159e-06 - accuracy: 1.0000 - val_loss: 14.1894 - val_accuracy: 0.3152
Epoch 8348/10000
1/1 [==============================] - 0s 112ms/step - loss: 3.8123e-06 - accuracy: 1.0000 - val_loss: 14.1901 - val_accuracy: 0.3152
Epoch 8349/10000
1/1 [==============================] - 0s 115ms/step - loss: 3.8132e-06 - accuracy: 1.0000 - val_loss: 14.1907 - val_accuracy: 0.3152
Epoch 8350/10000
1/1 [==============================] - 0s 111ms/step - loss: 3.8113e-06 - accuracy: 1.0000 - val_loss: 14.1915 - val_accuracy: 0.3154
Epoch 8351/10000
1/1 [==============================] - 0s 111ms/step - loss: 3.8078e-06 - accuracy: 1.0000 - val_loss: 14.1930 - val_accuracy: 0.3154
Epoch 8352/10000
1/1 [==============================] - 0s 115ms/step - loss: 3.8039e-06 - accuracy: 1.0000 - val_loss: 14.1944 - val_accuracy: 0.3153
Epoch 8353/10000
1/1 [==============================] - 0s 104ms/step - loss: 3.8028e-06 - accuracy: 1.0000 - val_loss: 14.1948 - val_accuracy: 0.3152
Epoch 8354/10000
1/1 [==============================] - 0s 103ms/step - loss: 3.7989e-06 - accuracy: 1.0000 - val_loss: 14.1943 - val_accuracy: 0.3152
Epoch 8355/10000
1/1 [==============================] - 0s 106ms/step - loss: 3.7987e-06 - accuracy: 1.0000 - val_loss: 14.1941 - val_accuracy: 0.3152
Epoch 8356/10000
1/1 [==============================] - 0s 107ms/step - loss: 3.7942e-06 - accuracy: 1.0000 - val_loss: 14.1948 - val_accuracy: 0.3152
Epoch 8357/10000
1/1 [==============================] - 0s 104ms/step - loss: 3.7925e-06 - accuracy: 1.0000 - val_loss: 14.1963 - val_accuracy: 0.3152
Epoch 8358/10000
1/1 [==============================] - 0s 107ms/step - loss: 3.7889e-06 - accuracy: 1.0000 - val_loss: 14.1980 - val_accuracy: 0.3151
Epoch 8359/10000
1/1 [==============================] - 0s 108ms/step - loss: 3.7870e-06 - accuracy: 1.0000 - val_loss: 14.1986 - val_accuracy: 0.3151
Epoch 8360/10000
1/1 [==============================] - 0s 102ms/step - loss: 3.7837e-06 - accuracy: 1.0000 - val_loss: 14.1984 - val_accuracy: 0.3152
Epoch 8361/10000
1/1 [==============================] - 0s 109ms/step - loss: 3.7820e-06 - accuracy: 1.0000 - val_loss: 14.1982 - val_accuracy: 0.3152
Epoch 8362/10000
1/1 [==============================] - 0s 115ms/step - loss: 3.7823e-06 - accuracy: 1.0000 - val_loss: 14.1984 - val_accuracy: 0.3153
Epoch 8363/10000
1/1 [==============================] - 0s 108ms/step - loss: 3.7787e-06 - accuracy: 1.0000 - val_loss: 14.1991 - val_accuracy: 0.3153
Epoch 8364/10000
1/1 [==============================] - 0s 128ms/step - loss: 3.7753e-06 - accuracy: 1.0000 - val_loss: 14.2004 - val_accuracy: 0.3152
Epoch 8365/10000
1/1 [==============================] - 0s 258ms/step - loss: 3.7720e-06 - accuracy: 1.0000 - val_loss: 14.2017 - val_accuracy: 0.3151
Epoch 8366/10000
1/1 [==============================] - 0s 248ms/step - loss: 3.7713e-06 - accuracy: 1.0000 - val_loss: 14.2026 - val_accuracy: 0.3152
Epoch 8367/10000
1/1 [==============================] - 0s 246ms/step - loss: 3.7720e-06 - accuracy: 1.0000 - val_loss: 14.2023 - val_accuracy: 0.3153
Epoch 8368/10000
1/1 [==============================] - 0s 142ms/step - loss: 3.7658e-06 - accuracy: 1.0000 - val_loss: 14.2024 - val_accuracy: 0.3152
Epoch 8369/10000
1/1 [==============================] - 0s 105ms/step - loss: 3.7632e-06 - accuracy: 1.0000 - val_loss: 14.2030 - val_accuracy: 0.3152
Epoch 8370/10000
1/1 [==============================] - 0s 107ms/step - loss: 3.7608e-06 - accuracy: 1.0000 - val_loss: 14.2039 - val_accuracy: 0.3152
Epoch 8371/10000
1/1 [==============================] - 0s 111ms/step - loss: 3.7598e-06 - accuracy: 1.0000 - val_loss: 14.2047 - val_accuracy: 0.3152
Epoch 8372/10000
1/1 [==============================] - 0s 105ms/step - loss: 3.7563e-06 - accuracy: 1.0000 - val_loss: 14.2058 - val_accuracy: 0.3153
Epoch 8373/10000
1/1 [==============================] - 0s 112ms/step - loss: 3.7539e-06 - accuracy: 1.0000 - val_loss: 14.2065 - val_accuracy: 0.3153
Epoch 8374/10000
1/1 [==============================] - 0s 103ms/step - loss: 3.7515e-06 - accuracy: 1.0000 - val_loss: 14.2068 - val_accuracy: 0.3152
Epoch 8375/10000
1/1 [==============================] - 0s 103ms/step - loss: 3.7508e-06 - accuracy: 1.0000 - val_loss: 14.2062 - val_accuracy: 0.3152
Epoch 8376/10000
1/1 [==============================] - 0s 113ms/step - loss: 3.7505e-06 - accuracy: 1.0000 - val_loss: 14.2064 - val_accuracy: 0.3152
Epoch 8377/10000
1/1 [==============================] - 0s 110ms/step - loss: 3.7472e-06 - accuracy: 1.0000 - val_loss: 14.2079 - val_accuracy: 0.3151
Epoch 8378/10000
1/1 [==============================] - 0s 105ms/step - loss: 3.7429e-06 - accuracy: 1.0000 - val_loss: 14.2093 - val_accuracy: 0.3152
Epoch 8379/10000
1/1 [==============================] - 0s 112ms/step - loss: 3.7408e-06 - accuracy: 1.0000 - val_loss: 14.2100 - val_accuracy: 0.3152
Epoch 8380/10000
1/1 [==============================] - 0s 110ms/step - loss: 3.7393e-06 - accuracy: 1.0000 - val_loss: 14.2101 - val_accuracy: 0.3154
Epoch 8381/10000
1/1 [==============================] - 0s 106ms/step - loss: 3.7343e-06 - accuracy: 1.0000 - val_loss: 14.2106 - val_accuracy: 0.3153
Epoch 8382/10000
1/1 [==============================] - 0s 104ms/step - loss: 3.7362e-06 - accuracy: 1.0000 - val_loss: 14.2112 - val_accuracy: 0.3151
Epoch 8383/10000
1/1 [==============================] - 0s 108ms/step - loss: 3.7334e-06 - accuracy: 1.0000 - val_loss: 14.2118 - val_accuracy: 0.3151
Epoch 8384/10000
1/1 [==============================] - 0s 108ms/step - loss: 3.7315e-06 - accuracy: 1.0000 - val_loss: 14.2123 - val_accuracy: 0.3151
Epoch 8385/10000
1/1 [==============================] - 0s 111ms/step - loss: 3.7288e-06 - accuracy: 1.0000 - val_loss: 14.2126 - val_accuracy: 0.3151
Epoch 8386/10000
1/1 [==============================] - 0s 115ms/step - loss: 3.7269e-06 - accuracy: 1.0000 - val_loss: 14.2136 - val_accuracy: 0.3152
Epoch 8387/10000
1/1 [==============================] - 0s 105ms/step - loss: 3.7241e-06 - accuracy: 1.0000 - val_loss: 14.2141 - val_accuracy: 0.3153
Epoch 8388/10000
1/1 [==============================] - 0s 105ms/step - loss: 3.7222e-06 - accuracy: 1.0000 - val_loss: 14.2144 - val_accuracy: 0.3153
Epoch 8389/10000
1/1 [==============================] - 0s 101ms/step - loss: 3.7200e-06 - accuracy: 1.0000 - val_loss: 14.2142 - val_accuracy: 0.3153
Epoch 8390/10000
1/1 [==============================] - 0s 107ms/step - loss: 3.7176e-06 - accuracy: 1.0000 - val_loss: 14.2144 - val_accuracy: 0.3153
Epoch 8391/10000
1/1 [==============================] - 0s 115ms/step - loss: 3.7162e-06 - accuracy: 1.0000 - val_loss: 14.2158 - val_accuracy: 0.3153
Epoch 8392/10000
1/1 [==============================] - 0s 110ms/step - loss: 3.7126e-06 - accuracy: 1.0000 - val_loss: 14.2174 - val_accuracy: 0.3152
Epoch 8393/10000
1/1 [==============================] - 0s 110ms/step - loss: 3.7119e-06 - accuracy: 1.0000 - val_loss: 14.2187 - val_accuracy: 0.3154
Epoch 8394/10000
1/1 [==============================] - 0s 115ms/step - loss: 3.7122e-06 - accuracy: 1.0000 - val_loss: 14.2183 - val_accuracy: 0.3152
Epoch 8395/10000
1/1 [==============================] - 0s 111ms/step - loss: 3.7083e-06 - accuracy: 1.0000 - val_loss: 14.2182 - val_accuracy: 0.3152
Epoch 8396/10000
1/1 [==============================] - 0s 106ms/step - loss: 3.7055e-06 - accuracy: 1.0000 - val_loss: 14.2185 - val_accuracy: 0.3152
Epoch 8397/10000
1/1 [==============================] - 0s 112ms/step - loss: 3.7048e-06 - accuracy: 1.0000 - val_loss: 14.2191 - val_accuracy: 0.3152
Epoch 8398/10000
1/1 [==============================] - 0s 104ms/step - loss: 3.7007e-06 - accuracy: 1.0000 - val_loss: 14.2199 - val_accuracy: 0.3152
Epoch 8399/10000
1/1 [==============================] - 0s 109ms/step - loss: 3.6974e-06 - accuracy: 1.0000 - val_loss: 14.2209 - val_accuracy: 0.3151
Epoch 8400/10000
1/1 [==============================] - 0s 109ms/step - loss: 3.6983e-06 - accuracy: 1.0000 - val_loss: 14.2222 - val_accuracy: 0.3154
Epoch 8401/10000
1/1 [==============================] - 0s 112ms/step - loss: 3.6928e-06 - accuracy: 1.0000 - val_loss: 14.2231 - val_accuracy: 0.3151
Epoch 8402/10000
1/1 [==============================] - 0s 107ms/step - loss: 3.6902e-06 - accuracy: 1.0000 - val_loss: 14.2228 - val_accuracy: 0.3153
Epoch 8403/10000
1/1 [==============================] - 0s 103ms/step - loss: 3.6897e-06 - accuracy: 1.0000 - val_loss: 14.2228 - val_accuracy: 0.3153
Epoch 8404/10000
1/1 [==============================] - 0s 105ms/step - loss: 3.6871e-06 - accuracy: 1.0000 - val_loss: 14.2237 - val_accuracy: 0.3154
Epoch 8405/10000
1/1 [==============================] - 0s 112ms/step - loss: 3.6855e-06 - accuracy: 1.0000 - val_loss: 14.2244 - val_accuracy: 0.3152
Epoch 8406/10000
1/1 [==============================] - 0s 107ms/step - loss: 3.6814e-06 - accuracy: 1.0000 - val_loss: 14.2256 - val_accuracy: 0.3152
Epoch 8407/10000
1/1 [==============================] - 0s 107ms/step - loss: 3.6773e-06 - accuracy: 1.0000 - val_loss: 14.2256 - val_accuracy: 0.3151
Epoch 8408/10000
1/1 [==============================] - 0s 108ms/step - loss: 3.6764e-06 - accuracy: 1.0000 - val_loss: 14.2259 - val_accuracy: 0.3152
Epoch 8409/10000
1/1 [==============================] - 0s 113ms/step - loss: 3.6776e-06 - accuracy: 1.0000 - val_loss: 14.2264 - val_accuracy: 0.3153
Epoch 8410/10000
1/1 [==============================] - 0s 102ms/step - loss: 3.6750e-06 - accuracy: 1.0000 - val_loss: 14.2274 - val_accuracy: 0.3153
Epoch 8411/10000
1/1 [==============================] - 0s 104ms/step - loss: 3.6716e-06 - accuracy: 1.0000 - val_loss: 14.2284 - val_accuracy: 0.3153
Epoch 8412/10000
1/1 [==============================] - 0s 103ms/step - loss: 3.6690e-06 - accuracy: 1.0000 - val_loss: 14.2292 - val_accuracy: 0.3152
Epoch 8413/10000
1/1 [==============================] - 0s 104ms/step - loss: 3.6654e-06 - accuracy: 1.0000 - val_loss: 14.2287 - val_accuracy: 0.3152
Epoch 8414/10000
1/1 [==============================] - 0s 103ms/step - loss: 3.6638e-06 - accuracy: 1.0000 - val_loss: 14.2286 - val_accuracy: 0.3152
Epoch 8415/10000
1/1 [==============================] - 0s 107ms/step - loss: 3.6640e-06 - accuracy: 1.0000 - val_loss: 14.2292 - val_accuracy: 0.3152
Epoch 8416/10000
1/1 [==============================] - 0s 104ms/step - loss: 3.6630e-06 - accuracy: 1.0000 - val_loss: 14.2302 - val_accuracy: 0.3153
Epoch 8417/10000
1/1 [==============================] - 0s 103ms/step - loss: 3.6607e-06 - accuracy: 1.0000 - val_loss: 14.2312 - val_accuracy: 0.3153
Epoch 8418/10000
1/1 [==============================] - 0s 102ms/step - loss: 3.6580e-06 - accuracy: 1.0000 - val_loss: 14.2324 - val_accuracy: 0.3153
Epoch 8419/10000
1/1 [==============================] - 0s 103ms/step - loss: 3.6545e-06 - accuracy: 1.0000 - val_loss: 14.2338 - val_accuracy: 0.3153
Epoch 8420/10000
1/1 [==============================] - 0s 107ms/step - loss: 3.6530e-06 - accuracy: 1.0000 - val_loss: 14.2341 - val_accuracy: 0.3151
Epoch 8421/10000
1/1 [==============================] - 0s 105ms/step - loss: 3.6506e-06 - accuracy: 1.0000 - val_loss: 14.2331 - val_accuracy: 0.3151
Epoch 8422/10000
1/1 [==============================] - 0s 106ms/step - loss: 3.6473e-06 - accuracy: 1.0000 - val_loss: 14.2334 - val_accuracy: 0.3153
Epoch 8423/10000
1/1 [==============================] - 0s 104ms/step - loss: 3.6452e-06 - accuracy: 1.0000 - val_loss: 14.2349 - val_accuracy: 0.3153
Epoch 8424/10000
1/1 [==============================] - 0s 102ms/step - loss: 3.6459e-06 - accuracy: 1.0000 - val_loss: 14.2357 - val_accuracy: 0.3152
Epoch 8425/10000
1/1 [==============================] - 0s 105ms/step - loss: 3.6440e-06 - accuracy: 1.0000 - val_loss: 14.2362 - val_accuracy: 0.3152
Epoch 8426/10000
1/1 [==============================] - 0s 104ms/step - loss: 3.6409e-06 - accuracy: 1.0000 - val_loss: 14.2372 - val_accuracy: 0.3154
Epoch 8427/10000
1/1 [==============================] - 0s 111ms/step - loss: 3.6382e-06 - accuracy: 1.0000 - val_loss: 14.2381 - val_accuracy: 0.3154
Epoch 8428/10000
1/1 [==============================] - 0s 112ms/step - loss: 3.6371e-06 - accuracy: 1.0000 - val_loss: 14.2381 - val_accuracy: 0.3152
Epoch 8429/10000
1/1 [==============================] - 0s 110ms/step - loss: 3.6354e-06 - accuracy: 1.0000 - val_loss: 14.2378 - val_accuracy: 0.3153
Epoch 8430/10000
1/1 [==============================] - 0s 108ms/step - loss: 3.6337e-06 - accuracy: 1.0000 - val_loss: 14.2383 - val_accuracy: 0.3152
Epoch 8431/10000
1/1 [==============================] - 0s 104ms/step - loss: 3.6287e-06 - accuracy: 1.0000 - val_loss: 14.2397 - val_accuracy: 0.3151
Epoch 8432/10000
1/1 [==============================] - 0s 117ms/step - loss: 3.6275e-06 - accuracy: 1.0000 - val_loss: 14.2410 - val_accuracy: 0.3153
Epoch 8433/10000
1/1 [==============================] - 0s 113ms/step - loss: 3.6242e-06 - accuracy: 1.0000 - val_loss: 14.2414 - val_accuracy: 0.3153
Epoch 8434/10000
1/1 [==============================] - 0s 115ms/step - loss: 3.6220e-06 - accuracy: 1.0000 - val_loss: 14.2414 - val_accuracy: 0.3153
Epoch 8435/10000
1/1 [==============================] - 0s 110ms/step - loss: 3.6220e-06 - accuracy: 1.0000 - val_loss: 14.2415 - val_accuracy: 0.3154
Epoch 8436/10000
1/1 [==============================] - 0s 118ms/step - loss: 3.6187e-06 - accuracy: 1.0000 - val_loss: 14.2425 - val_accuracy: 0.3152
Epoch 8437/10000
1/1 [==============================] - 0s 107ms/step - loss: 3.6170e-06 - accuracy: 1.0000 - val_loss: 14.2435 - val_accuracy: 0.3153
Epoch 8438/10000
1/1 [==============================] - 0s 104ms/step - loss: 3.6158e-06 - accuracy: 1.0000 - val_loss: 14.2443 - val_accuracy: 0.3153
Epoch 8439/10000
1/1 [==============================] - 0s 104ms/step - loss: 3.6118e-06 - accuracy: 1.0000 - val_loss: 14.2446 - val_accuracy: 0.3153
Epoch 8440/10000
1/1 [==============================] - 0s 106ms/step - loss: 3.6096e-06 - accuracy: 1.0000 - val_loss: 14.2452 - val_accuracy: 0.3152
Epoch 8441/10000
1/1 [==============================] - 0s 108ms/step - loss: 3.6061e-06 - accuracy: 1.0000 - val_loss: 14.2460 - val_accuracy: 0.3152
Epoch 8442/10000
1/1 [==============================] - 0s 107ms/step - loss: 3.6056e-06 - accuracy: 1.0000 - val_loss: 14.2460 - val_accuracy: 0.3152
Epoch 8443/10000
1/1 [==============================] - 0s 110ms/step - loss: 3.6013e-06 - accuracy: 1.0000 - val_loss: 14.2463 - val_accuracy: 0.3152
Epoch 8444/10000
1/1 [==============================] - 0s 105ms/step - loss: 3.5991e-06 - accuracy: 1.0000 - val_loss: 14.2475 - val_accuracy: 0.3152
Epoch 8445/10000
1/1 [==============================] - 0s 106ms/step - loss: 3.5984e-06 - accuracy: 1.0000 - val_loss: 14.2489 - val_accuracy: 0.3151
Epoch 8446/10000
1/1 [==============================] - 0s 103ms/step - loss: 3.5941e-06 - accuracy: 1.0000 - val_loss: 14.2496 - val_accuracy: 0.3153
Epoch 8447/10000
1/1 [==============================] - 0s 105ms/step - loss: 3.5941e-06 - accuracy: 1.0000 - val_loss: 14.2490 - val_accuracy: 0.3154
Epoch 8448/10000
1/1 [==============================] - 0s 102ms/step - loss: 3.5915e-06 - accuracy: 1.0000 - val_loss: 14.2492 - val_accuracy: 0.3153
Epoch 8449/10000
1/1 [==============================] - 0s 105ms/step - loss: 3.5898e-06 - accuracy: 1.0000 - val_loss: 14.2501 - val_accuracy: 0.3152
Epoch 8450/10000
1/1 [==============================] - 0s 106ms/step - loss: 3.5882e-06 - accuracy: 1.0000 - val_loss: 14.2514 - val_accuracy: 0.3151
Epoch 8451/10000
1/1 [==============================] - 0s 109ms/step - loss: 3.5827e-06 - accuracy: 1.0000 - val_loss: 14.2521 - val_accuracy: 0.3152
Epoch 8452/10000
1/1 [==============================] - 0s 106ms/step - loss: 3.5801e-06 - accuracy: 1.0000 - val_loss: 14.2525 - val_accuracy: 0.3152
Epoch 8453/10000
1/1 [==============================] - 0s 108ms/step - loss: 3.5801e-06 - accuracy: 1.0000 - val_loss: 14.2524 - val_accuracy: 0.3152
Epoch 8454/10000
1/1 [==============================] - 0s 109ms/step - loss: 3.5806e-06 - accuracy: 1.0000 - val_loss: 14.2524 - val_accuracy: 0.3152
Epoch 8455/10000
1/1 [==============================] - 0s 110ms/step - loss: 3.5777e-06 - accuracy: 1.0000 - val_loss: 14.2528 - val_accuracy: 0.3152
Epoch 8456/10000
1/1 [==============================] - 0s 115ms/step - loss: 3.5755e-06 - accuracy: 1.0000 - val_loss: 14.2535 - val_accuracy: 0.3153
Epoch 8457/10000
1/1 [==============================] - 0s 110ms/step - loss: 3.5739e-06 - accuracy: 1.0000 - val_loss: 14.2550 - val_accuracy: 0.3151
Epoch 8458/10000
1/1 [==============================] - 0s 116ms/step - loss: 3.5715e-06 - accuracy: 1.0000 - val_loss: 14.2566 - val_accuracy: 0.3152
Epoch 8459/10000
1/1 [==============================] - 0s 111ms/step - loss: 3.5722e-06 - accuracy: 1.0000 - val_loss: 14.2568 - val_accuracy: 0.3150
Epoch 8460/10000
1/1 [==============================] - 0s 107ms/step - loss: 3.5679e-06 - accuracy: 1.0000 - val_loss: 14.2560 - val_accuracy: 0.3153
Epoch 8461/10000
1/1 [==============================] - 0s 110ms/step - loss: 3.5646e-06 - accuracy: 1.0000 - val_loss: 14.2559 - val_accuracy: 0.3152
Epoch 8462/10000
1/1 [==============================] - 0s 111ms/step - loss: 3.5634e-06 - accuracy: 1.0000 - val_loss: 14.2570 - val_accuracy: 0.3151
Epoch 8463/10000
1/1 [==============================] - 0s 112ms/step - loss: 3.5605e-06 - accuracy: 1.0000 - val_loss: 14.2589 - val_accuracy: 0.3149
Epoch 8464/10000
1/1 [==============================] - 0s 112ms/step - loss: 3.5586e-06 - accuracy: 1.0000 - val_loss: 14.2600 - val_accuracy: 0.3149
Epoch 8465/10000
1/1 [==============================] - 0s 111ms/step - loss: 3.5569e-06 - accuracy: 1.0000 - val_loss: 14.2599 - val_accuracy: 0.3151
Epoch 8466/10000
1/1 [==============================] - 0s 106ms/step - loss: 3.5553e-06 - accuracy: 1.0000 - val_loss: 14.2593 - val_accuracy: 0.3153
Epoch 8467/10000
1/1 [==============================] - 0s 121ms/step - loss: 3.5546e-06 - accuracy: 1.0000 - val_loss: 14.2598 - val_accuracy: 0.3153
Epoch 8468/10000
1/1 [==============================] - 0s 119ms/step - loss: 3.5524e-06 - accuracy: 1.0000 - val_loss: 14.2609 - val_accuracy: 0.3152
Epoch 8469/10000
1/1 [==============================] - 0s 123ms/step - loss: 3.5510e-06 - accuracy: 1.0000 - val_loss: 14.2615 - val_accuracy: 0.3152
Epoch 8470/10000
1/1 [==============================] - 0s 113ms/step - loss: 3.5493e-06 - accuracy: 1.0000 - val_loss: 14.2624 - val_accuracy: 0.3151
Epoch 8471/10000
1/1 [==============================] - 0s 116ms/step - loss: 3.5448e-06 - accuracy: 1.0000 - val_loss: 14.2637 - val_accuracy: 0.3152
Epoch 8472/10000
1/1 [==============================] - 0s 110ms/step - loss: 3.5422e-06 - accuracy: 1.0000 - val_loss: 14.2645 - val_accuracy: 0.3151
Epoch 8473/10000
1/1 [==============================] - 0s 106ms/step - loss: 3.5398e-06 - accuracy: 1.0000 - val_loss: 14.2644 - val_accuracy: 0.3149
Epoch 8474/10000
1/1 [==============================] - 0s 110ms/step - loss: 3.5379e-06 - accuracy: 1.0000 - val_loss: 14.2643 - val_accuracy: 0.3153
Epoch 8475/10000
1/1 [==============================] - 0s 109ms/step - loss: 3.5350e-06 - accuracy: 1.0000 - val_loss: 14.2653 - val_accuracy: 0.3152
Epoch 8476/10000
1/1 [==============================] - 0s 117ms/step - loss: 3.5348e-06 - accuracy: 1.0000 - val_loss: 14.2668 - val_accuracy: 0.3151
Epoch 8477/10000
1/1 [==============================] - 0s 110ms/step - loss: 3.5319e-06 - accuracy: 1.0000 - val_loss: 14.2677 - val_accuracy: 0.3152
Epoch 8478/10000
1/1 [==============================] - 0s 102ms/step - loss: 3.5291e-06 - accuracy: 1.0000 - val_loss: 14.2673 - val_accuracy: 0.3152
Epoch 8479/10000
1/1 [==============================] - 0s 105ms/step - loss: 3.5267e-06 - accuracy: 1.0000 - val_loss: 14.2675 - val_accuracy: 0.3152
Epoch 8480/10000
1/1 [==============================] - 0s 105ms/step - loss: 3.5267e-06 - accuracy: 1.0000 - val_loss: 14.2686 - val_accuracy: 0.3149
Epoch 8481/10000
1/1 [==============================] - 0s 107ms/step - loss: 3.5245e-06 - accuracy: 1.0000 - val_loss: 14.2698 - val_accuracy: 0.3148
Epoch 8482/10000
1/1 [==============================] - 0s 107ms/step - loss: 3.5217e-06 - accuracy: 1.0000 - val_loss: 14.2698 - val_accuracy: 0.3150
Epoch 8483/10000
1/1 [==============================] - 0s 112ms/step - loss: 3.5207e-06 - accuracy: 1.0000 - val_loss: 14.2697 - val_accuracy: 0.3152
Epoch 8484/10000
1/1 [==============================] - 0s 102ms/step - loss: 3.5164e-06 - accuracy: 1.0000 - val_loss: 14.2697 - val_accuracy: 0.3152
Epoch 8485/10000
1/1 [==============================] - 0s 110ms/step - loss: 3.5164e-06 - accuracy: 1.0000 - val_loss: 14.2702 - val_accuracy: 0.3150
Epoch 8486/10000
1/1 [==============================] - 0s 117ms/step - loss: 3.5136e-06 - accuracy: 1.0000 - val_loss: 14.2710 - val_accuracy: 0.3151
Epoch 8487/10000
1/1 [==============================] - 0s 114ms/step - loss: 3.5105e-06 - accuracy: 1.0000 - val_loss: 14.2716 - val_accuracy: 0.3154
Epoch 8488/10000
1/1 [==============================] - 0s 111ms/step - loss: 3.5114e-06 - accuracy: 1.0000 - val_loss: 14.2730 - val_accuracy: 0.3151
Epoch 8489/10000
1/1 [==============================] - 0s 105ms/step - loss: 3.5085e-06 - accuracy: 1.0000 - val_loss: 14.2747 - val_accuracy: 0.3153
Epoch 8490/10000
1/1 [==============================] - 0s 102ms/step - loss: 3.5074e-06 - accuracy: 1.0000 - val_loss: 14.2753 - val_accuracy: 0.3151
Epoch 8491/10000
1/1 [==============================] - 0s 102ms/step - loss: 3.5014e-06 - accuracy: 1.0000 - val_loss: 14.2747 - val_accuracy: 0.3152
Epoch 8492/10000
1/1 [==============================] - 0s 109ms/step - loss: 3.4973e-06 - accuracy: 1.0000 - val_loss: 14.2746 - val_accuracy: 0.3153
Epoch 8493/10000
1/1 [==============================] - 0s 109ms/step - loss: 3.4976e-06 - accuracy: 1.0000 - val_loss: 14.2749 - val_accuracy: 0.3152
Epoch 8494/10000
1/1 [==============================] - 0s 102ms/step - loss: 3.4971e-06 - accuracy: 1.0000 - val_loss: 14.2758 - val_accuracy: 0.3151
Epoch 8495/10000
1/1 [==============================] - 0s 103ms/step - loss: 3.4969e-06 - accuracy: 1.0000 - val_loss: 14.2773 - val_accuracy: 0.3149
Epoch 8496/10000
1/1 [==============================] - 0s 102ms/step - loss: 3.4923e-06 - accuracy: 1.0000 - val_loss: 14.2786 - val_accuracy: 0.3148
Epoch 8497/10000
1/1 [==============================] - 0s 103ms/step - loss: 3.4911e-06 - accuracy: 1.0000 - val_loss: 14.2787 - val_accuracy: 0.3149
Epoch 8498/10000
1/1 [==============================] - 0s 101ms/step - loss: 3.4871e-06 - accuracy: 1.0000 - val_loss: 14.2787 - val_accuracy: 0.3152
Epoch 8499/10000
1/1 [==============================] - 0s 101ms/step - loss: 3.4845e-06 - accuracy: 1.0000 - val_loss: 14.2791 - val_accuracy: 0.3152
Epoch 8500/10000
1/1 [==============================] - 0s 103ms/step - loss: 3.4838e-06 - accuracy: 1.0000 - val_loss: 14.2801 - val_accuracy: 0.3152
Epoch 8501/10000
1/1 [==============================] - 0s 100ms/step - loss: 3.4816e-06 - accuracy: 1.0000 - val_loss: 14.2810 - val_accuracy: 0.3151
Epoch 8502/10000
1/1 [==============================] - 0s 102ms/step - loss: 3.4809e-06 - accuracy: 1.0000 - val_loss: 14.2819 - val_accuracy: 0.3149
Epoch 8503/10000
1/1 [==============================] - 0s 102ms/step - loss: 3.4778e-06 - accuracy: 1.0000 - val_loss: 14.2820 - val_accuracy: 0.3150
Epoch 8504/10000
1/1 [==============================] - 0s 103ms/step - loss: 3.4764e-06 - accuracy: 1.0000 - val_loss: 14.2823 - val_accuracy: 0.3151
Epoch 8505/10000
1/1 [==============================] - 0s 102ms/step - loss: 3.4728e-06 - accuracy: 1.0000 - val_loss: 14.2829 - val_accuracy: 0.3151
Epoch 8506/10000
1/1 [==============================] - 0s 104ms/step - loss: 3.4697e-06 - accuracy: 1.0000 - val_loss: 14.2837 - val_accuracy: 0.3151
Epoch 8507/10000
1/1 [==============================] - 0s 101ms/step - loss: 3.4690e-06 - accuracy: 1.0000 - val_loss: 14.2846 - val_accuracy: 0.3150
Epoch 8508/10000
1/1 [==============================] - 0s 103ms/step - loss: 3.4649e-06 - accuracy: 1.0000 - val_loss: 14.2852 - val_accuracy: 0.3150
Epoch 8509/10000
1/1 [==============================] - 0s 102ms/step - loss: 3.4644e-06 - accuracy: 1.0000 - val_loss: 14.2851 - val_accuracy: 0.3149
Epoch 8510/10000
1/1 [==============================] - 0s 106ms/step - loss: 3.4625e-06 - accuracy: 1.0000 - val_loss: 14.2855 - val_accuracy: 0.3152
Epoch 8511/10000
1/1 [==============================] - 0s 104ms/step - loss: 3.4590e-06 - accuracy: 1.0000 - val_loss: 14.2859 - val_accuracy: 0.3152
Epoch 8512/10000
1/1 [==============================] - 0s 100ms/step - loss: 3.4597e-06 - accuracy: 1.0000 - val_loss: 14.2866 - val_accuracy: 0.3153
Epoch 8513/10000
1/1 [==============================] - 0s 105ms/step - loss: 3.4573e-06 - accuracy: 1.0000 - val_loss: 14.2876 - val_accuracy: 0.3151
Epoch 8514/10000
1/1 [==============================] - 0s 101ms/step - loss: 3.4549e-06 - accuracy: 1.0000 - val_loss: 14.2890 - val_accuracy: 0.3150
Epoch 8515/10000
1/1 [==============================] - 0s 104ms/step - loss: 3.4535e-06 - accuracy: 1.0000 - val_loss: 14.2896 - val_accuracy: 0.3150
Epoch 8516/10000
1/1 [==============================] - 0s 103ms/step - loss: 3.4499e-06 - accuracy: 1.0000 - val_loss: 14.2893 - val_accuracy: 0.3152
Epoch 8517/10000
1/1 [==============================] - 0s 104ms/step - loss: 3.4485e-06 - accuracy: 1.0000 - val_loss: 14.2894 - val_accuracy: 0.3153
Epoch 8518/10000
1/1 [==============================] - 0s 102ms/step - loss: 3.4461e-06 - accuracy: 1.0000 - val_loss: 14.2905 - val_accuracy: 0.3149
Epoch 8519/10000
1/1 [==============================] - 0s 102ms/step - loss: 3.4432e-06 - accuracy: 1.0000 - val_loss: 14.2919 - val_accuracy: 0.3149
Epoch 8520/10000
1/1 [==============================] - 0s 101ms/step - loss: 3.4449e-06 - accuracy: 1.0000 - val_loss: 14.2923 - val_accuracy: 0.3151
Epoch 8521/10000
1/1 [==============================] - 0s 103ms/step - loss: 3.4408e-06 - accuracy: 1.0000 - val_loss: 14.2922 - val_accuracy: 0.3150
Epoch 8522/10000
1/1 [==============================] - 0s 106ms/step - loss: 3.4385e-06 - accuracy: 1.0000 - val_loss: 14.2925 - val_accuracy: 0.3152
Epoch 8523/10000
1/1 [==============================] - 0s 102ms/step - loss: 3.4368e-06 - accuracy: 1.0000 - val_loss: 14.2931 - val_accuracy: 0.3153
Epoch 8524/10000
1/1 [==============================] - 0s 105ms/step - loss: 3.4356e-06 - accuracy: 1.0000 - val_loss: 14.2937 - val_accuracy: 0.3152
Epoch 8525/10000
1/1 [==============================] - 0s 101ms/step - loss: 3.4337e-06 - accuracy: 1.0000 - val_loss: 14.2942 - val_accuracy: 0.3153
Epoch 8526/10000
1/1 [==============================] - 0s 104ms/step - loss: 3.4301e-06 - accuracy: 1.0000 - val_loss: 14.2953 - val_accuracy: 0.3150
Epoch 8527/10000
1/1 [==============================] - 0s 109ms/step - loss: 3.4265e-06 - accuracy: 1.0000 - val_loss: 14.2967 - val_accuracy: 0.3151
Epoch 8528/10000
1/1 [==============================] - 0s 102ms/step - loss: 3.4249e-06 - accuracy: 1.0000 - val_loss: 14.2973 - val_accuracy: 0.3148
Epoch 8529/10000
1/1 [==============================] - 0s 105ms/step - loss: 3.4234e-06 - accuracy: 1.0000 - val_loss: 14.2971 - val_accuracy: 0.3153
Epoch 8530/10000
1/1 [==============================] - 0s 103ms/step - loss: 3.4220e-06 - accuracy: 1.0000 - val_loss: 14.2965 - val_accuracy: 0.3152
Epoch 8531/10000
1/1 [==============================] - 0s 102ms/step - loss: 3.4177e-06 - accuracy: 1.0000 - val_loss: 14.2971 - val_accuracy: 0.3152
Epoch 8532/10000
1/1 [==============================] - 0s 110ms/step - loss: 3.4189e-06 - accuracy: 1.0000 - val_loss: 14.2987 - val_accuracy: 0.3151
Epoch 8533/10000
1/1 [==============================] - 0s 107ms/step - loss: 3.4139e-06 - accuracy: 1.0000 - val_loss: 14.3005 - val_accuracy: 0.3151
Epoch 8534/10000
1/1 [==============================] - 0s 110ms/step - loss: 3.4137e-06 - accuracy: 1.0000 - val_loss: 14.3008 - val_accuracy: 0.3152
Epoch 8535/10000
1/1 [==============================] - 0s 106ms/step - loss: 3.4089e-06 - accuracy: 1.0000 - val_loss: 14.3004 - val_accuracy: 0.3152
Epoch 8536/10000
1/1 [==============================] - 0s 102ms/step - loss: 3.4082e-06 - accuracy: 1.0000 - val_loss: 14.3006 - val_accuracy: 0.3152
Epoch 8537/10000
1/1 [==============================] - 0s 102ms/step - loss: 3.4070e-06 - accuracy: 1.0000 - val_loss: 14.3015 - val_accuracy: 0.3152
Epoch 8538/10000
1/1 [==============================] - 0s 105ms/step - loss: 3.4046e-06 - accuracy: 1.0000 - val_loss: 14.3025 - val_accuracy: 0.3151
Epoch 8539/10000
1/1 [==============================] - 0s 104ms/step - loss: 3.4022e-06 - accuracy: 1.0000 - val_loss: 14.3033 - val_accuracy: 0.3152
Epoch 8540/10000
1/1 [==============================] - 0s 104ms/step - loss: 3.4020e-06 - accuracy: 1.0000 - val_loss: 14.3036 - val_accuracy: 0.3151
Epoch 8541/10000
1/1 [==============================] - 0s 98ms/step - loss: 3.3982e-06 - accuracy: 1.0000 - val_loss: 14.3041 - val_accuracy: 0.3152
Epoch 8542/10000
1/1 [==============================] - 0s 106ms/step - loss: 3.3967e-06 - accuracy: 1.0000 - val_loss: 14.3049 - val_accuracy: 0.3152
Epoch 8543/10000
1/1 [==============================] - 0s 110ms/step - loss: 3.3936e-06 - accuracy: 1.0000 - val_loss: 14.3053 - val_accuracy: 0.3152
Epoch 8544/10000
1/1 [==============================] - 0s 105ms/step - loss: 3.3920e-06 - accuracy: 1.0000 - val_loss: 14.3059 - val_accuracy: 0.3151
Epoch 8545/10000
1/1 [==============================] - 0s 110ms/step - loss: 3.3896e-06 - accuracy: 1.0000 - val_loss: 14.3062 - val_accuracy: 0.3149
Epoch 8546/10000
1/1 [==============================] - 0s 103ms/step - loss: 3.3881e-06 - accuracy: 1.0000 - val_loss: 14.3065 - val_accuracy: 0.3152
Epoch 8547/10000
1/1 [==============================] - 0s 107ms/step - loss: 3.3870e-06 - accuracy: 1.0000 - val_loss: 14.3068 - val_accuracy: 0.3153
Epoch 8548/10000
1/1 [==============================] - 0s 108ms/step - loss: 3.3831e-06 - accuracy: 1.0000 - val_loss: 14.3077 - val_accuracy: 0.3152
Epoch 8549/10000
1/1 [==============================] - 0s 103ms/step - loss: 3.3805e-06 - accuracy: 1.0000 - val_loss: 14.3092 - val_accuracy: 0.3152
Epoch 8550/10000
1/1 [==============================] - 0s 109ms/step - loss: 3.3774e-06 - accuracy: 1.0000 - val_loss: 14.3102 - val_accuracy: 0.3152
Epoch 8551/10000
1/1 [==============================] - 0s 118ms/step - loss: 3.3772e-06 - accuracy: 1.0000 - val_loss: 14.3096 - val_accuracy: 0.3151
Epoch 8552/10000
1/1 [==============================] - 0s 112ms/step - loss: 3.3753e-06 - accuracy: 1.0000 - val_loss: 14.3091 - val_accuracy: 0.3154
Epoch 8553/10000
1/1 [==============================] - 0s 105ms/step - loss: 3.3755e-06 - accuracy: 1.0000 - val_loss: 14.3099 - val_accuracy: 0.3154
Epoch 8554/10000
1/1 [==============================] - 0s 103ms/step - loss: 3.3734e-06 - accuracy: 1.0000 - val_loss: 14.3111 - val_accuracy: 0.3154
Epoch 8555/10000
1/1 [==============================] - 0s 109ms/step - loss: 3.3693e-06 - accuracy: 1.0000 - val_loss: 14.3124 - val_accuracy: 0.3153
Epoch 8556/10000
1/1 [==============================] - 0s 99ms/step - loss: 3.3655e-06 - accuracy: 1.0000 - val_loss: 14.3134 - val_accuracy: 0.3152
Epoch 8557/10000
1/1 [==============================] - 0s 101ms/step - loss: 3.3672e-06 - accuracy: 1.0000 - val_loss: 14.3139 - val_accuracy: 0.3152
Epoch 8558/10000
1/1 [==============================] - 0s 107ms/step - loss: 3.3650e-06 - accuracy: 1.0000 - val_loss: 14.3141 - val_accuracy: 0.3152
Epoch 8559/10000
1/1 [==============================] - 0s 104ms/step - loss: 3.3612e-06 - accuracy: 1.0000 - val_loss: 14.3145 - val_accuracy: 0.3152
Epoch 8560/10000
1/1 [==============================] - 0s 109ms/step - loss: 3.3595e-06 - accuracy: 1.0000 - val_loss: 14.3146 - val_accuracy: 0.3151
Epoch 8561/10000
1/1 [==============================] - 0s 103ms/step - loss: 3.3574e-06 - accuracy: 1.0000 - val_loss: 14.3152 - val_accuracy: 0.3152
Epoch 8562/10000
1/1 [==============================] - 0s 103ms/step - loss: 3.3548e-06 - accuracy: 1.0000 - val_loss: 14.3166 - val_accuracy: 0.3153
Epoch 8563/10000
1/1 [==============================] - 0s 107ms/step - loss: 3.3533e-06 - accuracy: 1.0000 - val_loss: 14.3178 - val_accuracy: 0.3152
Epoch 8564/10000
1/1 [==============================] - 0s 110ms/step - loss: 3.3529e-06 - accuracy: 1.0000 - val_loss: 14.3176 - val_accuracy: 0.3150
Epoch 8565/10000
1/1 [==============================] - 0s 104ms/step - loss: 3.3490e-06 - accuracy: 1.0000 - val_loss: 14.3179 - val_accuracy: 0.3151
Epoch 8566/10000
1/1 [==============================] - 0s 105ms/step - loss: 3.3469e-06 - accuracy: 1.0000 - val_loss: 14.3187 - val_accuracy: 0.3150
Epoch 8567/10000
1/1 [==============================] - 0s 103ms/step - loss: 3.3459e-06 - accuracy: 1.0000 - val_loss: 14.3192 - val_accuracy: 0.3152
Epoch 8568/10000
1/1 [==============================] - 0s 109ms/step - loss: 3.3429e-06 - accuracy: 1.0000 - val_loss: 14.3200 - val_accuracy: 0.3151
Epoch 8569/10000
1/1 [==============================] - 0s 104ms/step - loss: 3.3426e-06 - accuracy: 1.0000 - val_loss: 14.3208 - val_accuracy: 0.3152
Epoch 8570/10000
1/1 [==============================] - 0s 113ms/step - loss: 3.3436e-06 - accuracy: 1.0000 - val_loss: 14.3208 - val_accuracy: 0.3151
Epoch 8571/10000
1/1 [==============================] - 0s 103ms/step - loss: 3.3398e-06 - accuracy: 1.0000 - val_loss: 14.3211 - val_accuracy: 0.3154
Epoch 8572/10000
1/1 [==============================] - 0s 109ms/step - loss: 3.3376e-06 - accuracy: 1.0000 - val_loss: 14.3213 - val_accuracy: 0.3152
Epoch 8573/10000
1/1 [==============================] - 0s 106ms/step - loss: 3.3357e-06 - accuracy: 1.0000 - val_loss: 14.3219 - val_accuracy: 0.3151
Epoch 8574/10000
1/1 [==============================] - 0s 108ms/step - loss: 3.3357e-06 - accuracy: 1.0000 - val_loss: 14.3227 - val_accuracy: 0.3150
Epoch 8575/10000
1/1 [==============================] - 0s 109ms/step - loss: 3.3324e-06 - accuracy: 1.0000 - val_loss: 14.3238 - val_accuracy: 0.3152
Epoch 8576/10000
1/1 [==============================] - 0s 104ms/step - loss: 3.3293e-06 - accuracy: 1.0000 - val_loss: 14.3249 - val_accuracy: 0.3151
Epoch 8577/10000
1/1 [==============================] - 0s 102ms/step - loss: 3.3300e-06 - accuracy: 1.0000 - val_loss: 14.3253 - val_accuracy: 0.3152
Epoch 8578/10000
1/1 [==============================] - 0s 117ms/step - loss: 3.3276e-06 - accuracy: 1.0000 - val_loss: 14.3251 - val_accuracy: 0.3152
Epoch 8579/10000
1/1 [==============================] - 0s 102ms/step - loss: 3.3247e-06 - accuracy: 1.0000 - val_loss: 14.3256 - val_accuracy: 0.3150
Epoch 8580/10000
1/1 [==============================] - 0s 108ms/step - loss: 3.3235e-06 - accuracy: 1.0000 - val_loss: 14.3267 - val_accuracy: 0.3150
Epoch 8581/10000
1/1 [==============================] - 0s 111ms/step - loss: 3.3207e-06 - accuracy: 1.0000 - val_loss: 14.3276 - val_accuracy: 0.3153
Epoch 8582/10000
1/1 [==============================] - 0s 108ms/step - loss: 3.3190e-06 - accuracy: 1.0000 - val_loss: 14.3282 - val_accuracy: 0.3151
Epoch 8583/10000
1/1 [==============================] - 0s 104ms/step - loss: 3.3173e-06 - accuracy: 1.0000 - val_loss: 14.3289 - val_accuracy: 0.3152
Epoch 8584/10000
1/1 [==============================] - 0s 108ms/step - loss: 3.3154e-06 - accuracy: 1.0000 - val_loss: 14.3290 - val_accuracy: 0.3150
Epoch 8585/10000
1/1 [==============================] - 0s 110ms/step - loss: 3.3111e-06 - accuracy: 1.0000 - val_loss: 14.3296 - val_accuracy: 0.3150
Epoch 8586/10000
1/1 [==============================] - 0s 105ms/step - loss: 3.3116e-06 - accuracy: 1.0000 - val_loss: 14.3307 - val_accuracy: 0.3150
Epoch 8587/10000
1/1 [==============================] - 0s 105ms/step - loss: 3.3088e-06 - accuracy: 1.0000 - val_loss: 14.3314 - val_accuracy: 0.3150
Epoch 8588/10000
1/1 [==============================] - 0s 110ms/step - loss: 3.3068e-06 - accuracy: 1.0000 - val_loss: 14.3320 - val_accuracy: 0.3154
Epoch 8589/10000
1/1 [==============================] - 0s 105ms/step - loss: 3.3037e-06 - accuracy: 1.0000 - val_loss: 14.3320 - val_accuracy: 0.3152
Epoch 8590/10000
1/1 [==============================] - 0s 105ms/step - loss: 3.3011e-06 - accuracy: 1.0000 - val_loss: 14.3322 - val_accuracy: 0.3150
Epoch 8591/10000
1/1 [==============================] - 0s 105ms/step - loss: 3.3007e-06 - accuracy: 1.0000 - val_loss: 14.3327 - val_accuracy: 0.3152
Epoch 8592/10000
1/1 [==============================] - 0s 106ms/step - loss: 3.2973e-06 - accuracy: 1.0000 - val_loss: 14.3339 - val_accuracy: 0.3150
Epoch 8593/10000
1/1 [==============================] - 0s 104ms/step - loss: 3.2976e-06 - accuracy: 1.0000 - val_loss: 14.3351 - val_accuracy: 0.3151
Epoch 8594/10000
1/1 [==============================] - 0s 112ms/step - loss: 3.2976e-06 - accuracy: 1.0000 - val_loss: 14.3349 - val_accuracy: 0.3152
Epoch 8595/10000
1/1 [==============================] - 0s 102ms/step - loss: 3.2954e-06 - accuracy: 1.0000 - val_loss: 14.3349 - val_accuracy: 0.3152
Epoch 8596/10000
1/1 [==============================] - 0s 103ms/step - loss: 3.2918e-06 - accuracy: 1.0000 - val_loss: 14.3355 - val_accuracy: 0.3152
Epoch 8597/10000
1/1 [==============================] - 0s 108ms/step - loss: 3.2897e-06 - accuracy: 1.0000 - val_loss: 14.3363 - val_accuracy: 0.3151
Epoch 8598/10000
1/1 [==============================] - 0s 104ms/step - loss: 3.2878e-06 - accuracy: 1.0000 - val_loss: 14.3375 - val_accuracy: 0.3154
Epoch 8599/10000
1/1 [==============================] - 0s 105ms/step - loss: 3.2863e-06 - accuracy: 1.0000 - val_loss: 14.3385 - val_accuracy: 0.3152
Epoch 8600/10000
1/1 [==============================] - 0s 109ms/step - loss: 3.2863e-06 - accuracy: 1.0000 - val_loss: 14.3383 - val_accuracy: 0.3151
Epoch 8601/10000
1/1 [==============================] - 0s 103ms/step - loss: 3.2840e-06 - accuracy: 1.0000 - val_loss: 14.3383 - val_accuracy: 0.3151
Epoch 8602/10000
1/1 [==============================] - 0s 105ms/step - loss: 3.2809e-06 - accuracy: 1.0000 - val_loss: 14.3394 - val_accuracy: 0.3152
Epoch 8603/10000
1/1 [==============================] - 0s 112ms/step - loss: 3.2794e-06 - accuracy: 1.0000 - val_loss: 14.3408 - val_accuracy: 0.3151
Epoch 8604/10000
1/1 [==============================] - 0s 103ms/step - loss: 3.2780e-06 - accuracy: 1.0000 - val_loss: 14.3410 - val_accuracy: 0.3152
Epoch 8605/10000
1/1 [==============================] - 0s 105ms/step - loss: 3.2735e-06 - accuracy: 1.0000 - val_loss: 14.3410 - val_accuracy: 0.3150
Epoch 8606/10000
1/1 [==============================] - 0s 102ms/step - loss: 3.2716e-06 - accuracy: 1.0000 - val_loss: 14.3413 - val_accuracy: 0.3152
Epoch 8607/10000
1/1 [==============================] - 0s 106ms/step - loss: 3.2706e-06 - accuracy: 1.0000 - val_loss: 14.3423 - val_accuracy: 0.3152
Epoch 8608/10000
1/1 [==============================] - 0s 103ms/step - loss: 3.2704e-06 - accuracy: 1.0000 - val_loss: 14.3436 - val_accuracy: 0.3151
Epoch 8609/10000
1/1 [==============================] - 0s 104ms/step - loss: 3.2682e-06 - accuracy: 1.0000 - val_loss: 14.3441 - val_accuracy: 0.3150
Epoch 8610/10000
1/1 [==============================] - 0s 107ms/step - loss: 3.2656e-06 - accuracy: 1.0000 - val_loss: 14.3437 - val_accuracy: 0.3151
Epoch 8611/10000
1/1 [==============================] - 0s 105ms/step - loss: 3.2625e-06 - accuracy: 1.0000 - val_loss: 14.3441 - val_accuracy: 0.3154
Epoch 8612/10000
1/1 [==============================] - 0s 106ms/step - loss: 3.2613e-06 - accuracy: 1.0000 - val_loss: 14.3446 - val_accuracy: 0.3154
Epoch 8613/10000
1/1 [==============================] - 0s 103ms/step - loss: 3.2587e-06 - accuracy: 1.0000 - val_loss: 14.3453 - val_accuracy: 0.3152
Epoch 8614/10000
1/1 [==============================] - 0s 101ms/step - loss: 3.2596e-06 - accuracy: 1.0000 - val_loss: 14.3462 - val_accuracy: 0.3153
Epoch 8615/10000
1/1 [==============================] - 0s 103ms/step - loss: 3.2558e-06 - accuracy: 1.0000 - val_loss: 14.3469 - val_accuracy: 0.3153
Epoch 8616/10000
1/1 [==============================] - 0s 107ms/step - loss: 3.2520e-06 - accuracy: 1.0000 - val_loss: 14.3484 - val_accuracy: 0.3152
Epoch 8617/10000
1/1 [==============================] - 0s 107ms/step - loss: 3.2523e-06 - accuracy: 1.0000 - val_loss: 14.3487 - val_accuracy: 0.3153
Epoch 8618/10000
1/1 [==============================] - 0s 107ms/step - loss: 3.2492e-06 - accuracy: 1.0000 - val_loss: 14.3488 - val_accuracy: 0.3153
Epoch 8619/10000
1/1 [==============================] - 0s 104ms/step - loss: 3.2487e-06 - accuracy: 1.0000 - val_loss: 14.3486 - val_accuracy: 0.3154
Epoch 8620/10000
1/1 [==============================] - 0s 103ms/step - loss: 3.2470e-06 - accuracy: 1.0000 - val_loss: 14.3491 - val_accuracy: 0.3154
Epoch 8621/10000
1/1 [==============================] - 0s 107ms/step - loss: 3.2463e-06 - accuracy: 1.0000 - val_loss: 14.3505 - val_accuracy: 0.3152
Epoch 8622/10000
1/1 [==============================] - 0s 108ms/step - loss: 3.2425e-06 - accuracy: 1.0000 - val_loss: 14.3516 - val_accuracy: 0.3152
Epoch 8623/10000
1/1 [==============================] - 0s 112ms/step - loss: 3.2396e-06 - accuracy: 1.0000 - val_loss: 14.3527 - val_accuracy: 0.3151
Epoch 8624/10000
1/1 [==============================] - 0s 102ms/step - loss: 3.2410e-06 - accuracy: 1.0000 - val_loss: 14.3526 - val_accuracy: 0.3152
Epoch 8625/10000
1/1 [==============================] - 0s 102ms/step - loss: 3.2387e-06 - accuracy: 1.0000 - val_loss: 14.3526 - val_accuracy: 0.3152
Epoch 8626/10000
1/1 [==============================] - 0s 106ms/step - loss: 3.2363e-06 - accuracy: 1.0000 - val_loss: 14.3531 - val_accuracy: 0.3154
Epoch 8627/10000
1/1 [==============================] - 0s 105ms/step - loss: 3.2341e-06 - accuracy: 1.0000 - val_loss: 14.3540 - val_accuracy: 0.3154
Epoch 8628/10000
1/1 [==============================] - 0s 104ms/step - loss: 3.2313e-06 - accuracy: 1.0000 - val_loss: 14.3548 - val_accuracy: 0.3152
Epoch 8629/10000
1/1 [==============================] - 0s 105ms/step - loss: 3.2296e-06 - accuracy: 1.0000 - val_loss: 14.3558 - val_accuracy: 0.3152
Epoch 8630/10000
1/1 [==============================] - 0s 107ms/step - loss: 3.2279e-06 - accuracy: 1.0000 - val_loss: 14.3563 - val_accuracy: 0.3153
Epoch 8631/10000
1/1 [==============================] - 0s 108ms/step - loss: 3.2251e-06 - accuracy: 1.0000 - val_loss: 14.3566 - val_accuracy: 0.3152
Epoch 8632/10000
1/1 [==============================] - 0s 106ms/step - loss: 3.2248e-06 - accuracy: 1.0000 - val_loss: 14.3567 - val_accuracy: 0.3152
Epoch 8633/10000
1/1 [==============================] - 0s 108ms/step - loss: 3.2225e-06 - accuracy: 1.0000 - val_loss: 14.3572 - val_accuracy: 0.3153
Epoch 8634/10000
1/1 [==============================] - 0s 110ms/step - loss: 3.2186e-06 - accuracy: 1.0000 - val_loss: 14.3583 - val_accuracy: 0.3154
Epoch 8635/10000
1/1 [==============================] - 0s 108ms/step - loss: 3.2182e-06 - accuracy: 1.0000 - val_loss: 14.3595 - val_accuracy: 0.3154
Epoch 8636/10000
1/1 [==============================] - 0s 107ms/step - loss: 3.2160e-06 - accuracy: 1.0000 - val_loss: 14.3597 - val_accuracy: 0.3154
Epoch 8637/10000
1/1 [==============================] - 0s 106ms/step - loss: 3.2134e-06 - accuracy: 1.0000 - val_loss: 14.3598 - val_accuracy: 0.3152
Epoch 8638/10000
1/1 [==============================] - 0s 106ms/step - loss: 3.2124e-06 - accuracy: 1.0000 - val_loss: 14.3601 - val_accuracy: 0.3152
Epoch 8639/10000
1/1 [==============================] - 0s 106ms/step - loss: 3.2108e-06 - accuracy: 1.0000 - val_loss: 14.3613 - val_accuracy: 0.3152
Epoch 8640/10000
1/1 [==============================] - 0s 105ms/step - loss: 3.2084e-06 - accuracy: 1.0000 - val_loss: 14.3620 - val_accuracy: 0.3153
Epoch 8641/10000
1/1 [==============================] - 0s 106ms/step - loss: 3.2048e-06 - accuracy: 1.0000 - val_loss: 14.3624 - val_accuracy: 0.3155
Epoch 8642/10000
1/1 [==============================] - 0s 107ms/step - loss: 3.2039e-06 - accuracy: 1.0000 - val_loss: 14.3627 - val_accuracy: 0.3154
Epoch 8643/10000
1/1 [==============================] - 0s 108ms/step - loss: 3.2017e-06 - accuracy: 1.0000 - val_loss: 14.3633 - val_accuracy: 0.3153
Epoch 8644/10000
1/1 [==============================] - 0s 106ms/step - loss: 3.2015e-06 - accuracy: 1.0000 - val_loss: 14.3641 - val_accuracy: 0.3155
Epoch 8645/10000
1/1 [==============================] - 0s 107ms/step - loss: 3.1984e-06 - accuracy: 1.0000 - val_loss: 14.3648 - val_accuracy: 0.3155
Epoch 8646/10000
1/1 [==============================] - 0s 111ms/step - loss: 3.1955e-06 - accuracy: 1.0000 - val_loss: 14.3650 - val_accuracy: 0.3153
Epoch 8647/10000
1/1 [==============================] - 0s 115ms/step - loss: 3.1936e-06 - accuracy: 1.0000 - val_loss: 14.3654 - val_accuracy: 0.3153
Epoch 8648/10000
1/1 [==============================] - 0s 106ms/step - loss: 3.1934e-06 - accuracy: 1.0000 - val_loss: 14.3658 - val_accuracy: 0.3153
Epoch 8649/10000
1/1 [==============================] - 0s 111ms/step - loss: 3.1891e-06 - accuracy: 1.0000 - val_loss: 14.3667 - val_accuracy: 0.3154
Epoch 8650/10000
1/1 [==============================] - 0s 107ms/step - loss: 3.1867e-06 - accuracy: 1.0000 - val_loss: 14.3682 - val_accuracy: 0.3153
Epoch 8651/10000
1/1 [==============================] - 0s 103ms/step - loss: 3.1853e-06 - accuracy: 1.0000 - val_loss: 14.3690 - val_accuracy: 0.3153
Epoch 8652/10000
1/1 [==============================] - 0s 102ms/step - loss: 3.1836e-06 - accuracy: 1.0000 - val_loss: 14.3687 - val_accuracy: 0.3154
Epoch 8653/10000
1/1 [==============================] - 0s 103ms/step - loss: 3.1814e-06 - accuracy: 1.0000 - val_loss: 14.3689 - val_accuracy: 0.3152
Epoch 8654/10000
1/1 [==============================] - 0s 104ms/step - loss: 3.1800e-06 - accuracy: 1.0000 - val_loss: 14.3699 - val_accuracy: 0.3154
Epoch 8655/10000
1/1 [==============================] - 0s 108ms/step - loss: 3.1786e-06 - accuracy: 1.0000 - val_loss: 14.3711 - val_accuracy: 0.3154
Epoch 8656/10000
1/1 [==============================] - 0s 103ms/step - loss: 3.1767e-06 - accuracy: 1.0000 - val_loss: 14.3713 - val_accuracy: 0.3153
Epoch 8657/10000
1/1 [==============================] - 0s 103ms/step - loss: 3.1729e-06 - accuracy: 1.0000 - val_loss: 14.3716 - val_accuracy: 0.3153
Epoch 8658/10000
1/1 [==============================] - 0s 103ms/step - loss: 3.1738e-06 - accuracy: 1.0000 - val_loss: 14.3719 - val_accuracy: 0.3153
Epoch 8659/10000
1/1 [==============================] - 0s 112ms/step - loss: 3.1719e-06 - accuracy: 1.0000 - val_loss: 14.3726 - val_accuracy: 0.3153
Epoch 8660/10000
1/1 [==============================] - 0s 116ms/step - loss: 3.1702e-06 - accuracy: 1.0000 - val_loss: 14.3732 - val_accuracy: 0.3153
Epoch 8661/10000
1/1 [==============================] - 0s 108ms/step - loss: 3.1671e-06 - accuracy: 1.0000 - val_loss: 14.3745 - val_accuracy: 0.3154
Epoch 8662/10000
1/1 [==============================] - 0s 102ms/step - loss: 3.1645e-06 - accuracy: 1.0000 - val_loss: 14.3754 - val_accuracy: 0.3154
Epoch 8663/10000
1/1 [==============================] - 0s 104ms/step - loss: 3.1602e-06 - accuracy: 1.0000 - val_loss: 14.3749 - val_accuracy: 0.3154
Epoch 8664/10000
1/1 [==============================] - 0s 103ms/step - loss: 3.1595e-06 - accuracy: 1.0000 - val_loss: 14.3749 - val_accuracy: 0.3153
Epoch 8665/10000
1/1 [==============================] - 0s 104ms/step - loss: 3.1590e-06 - accuracy: 1.0000 - val_loss: 14.3756 - val_accuracy: 0.3153
Epoch 8666/10000
1/1 [==============================] - 0s 107ms/step - loss: 3.1574e-06 - accuracy: 1.0000 - val_loss: 14.3768 - val_accuracy: 0.3153
Epoch 8667/10000
1/1 [==============================] - 0s 106ms/step - loss: 3.1550e-06 - accuracy: 1.0000 - val_loss: 14.3782 - val_accuracy: 0.3153
Epoch 8668/10000
1/1 [==============================] - 0s 104ms/step - loss: 3.1521e-06 - accuracy: 1.0000 - val_loss: 14.3782 - val_accuracy: 0.3152
Epoch 8669/10000
1/1 [==============================] - 0s 108ms/step - loss: 3.1512e-06 - accuracy: 1.0000 - val_loss: 14.3781 - val_accuracy: 0.3153
Epoch 8670/10000
1/1 [==============================] - 0s 111ms/step - loss: 3.1512e-06 - accuracy: 1.0000 - val_loss: 14.3787 - val_accuracy: 0.3154
Epoch 8671/10000
1/1 [==============================] - 0s 104ms/step - loss: 3.1483e-06 - accuracy: 1.0000 - val_loss: 14.3798 - val_accuracy: 0.3156
Epoch 8672/10000
1/1 [==============================] - 0s 107ms/step - loss: 3.1445e-06 - accuracy: 1.0000 - val_loss: 14.3811 - val_accuracy: 0.3155
Epoch 8673/10000
1/1 [==============================] - 0s 104ms/step - loss: 3.1428e-06 - accuracy: 1.0000 - val_loss: 14.3812 - val_accuracy: 0.3155
Epoch 8674/10000
1/1 [==============================] - 0s 105ms/step - loss: 3.1414e-06 - accuracy: 1.0000 - val_loss: 14.3813 - val_accuracy: 0.3152
Epoch 8675/10000
1/1 [==============================] - 0s 108ms/step - loss: 3.1419e-06 - accuracy: 1.0000 - val_loss: 14.3819 - val_accuracy: 0.3154
Epoch 8676/10000
1/1 [==============================] - 0s 104ms/step - loss: 3.1402e-06 - accuracy: 1.0000 - val_loss: 14.3830 - val_accuracy: 0.3153
Epoch 8677/10000
1/1 [==============================] - 0s 118ms/step - loss: 3.1359e-06 - accuracy: 1.0000 - val_loss: 14.3836 - val_accuracy: 0.3154
Epoch 8678/10000
1/1 [==============================] - 0s 111ms/step - loss: 3.1333e-06 - accuracy: 1.0000 - val_loss: 14.3834 - val_accuracy: 0.3153
Epoch 8679/10000
1/1 [==============================] - 0s 109ms/step - loss: 3.1326e-06 - accuracy: 1.0000 - val_loss: 14.3838 - val_accuracy: 0.3153
Epoch 8680/10000
1/1 [==============================] - 0s 114ms/step - loss: 3.1299e-06 - accuracy: 1.0000 - val_loss: 14.3849 - val_accuracy: 0.3153
Epoch 8681/10000
1/1 [==============================] - 0s 109ms/step - loss: 3.1304e-06 - accuracy: 1.0000 - val_loss: 14.3860 - val_accuracy: 0.3152
Epoch 8682/10000
1/1 [==============================] - 0s 103ms/step - loss: 3.1259e-06 - accuracy: 1.0000 - val_loss: 14.3864 - val_accuracy: 0.3155
Epoch 8683/10000
1/1 [==============================] - 0s 105ms/step - loss: 3.1273e-06 - accuracy: 1.0000 - val_loss: 14.3867 - val_accuracy: 0.3155
Epoch 8684/10000
1/1 [==============================] - 0s 108ms/step - loss: 3.1252e-06 - accuracy: 1.0000 - val_loss: 14.3871 - val_accuracy: 0.3156
Epoch 8685/10000
1/1 [==============================] - 0s 110ms/step - loss: 3.1233e-06 - accuracy: 1.0000 - val_loss: 14.3880 - val_accuracy: 0.3154
Epoch 8686/10000
1/1 [==============================] - 0s 115ms/step - loss: 3.1190e-06 - accuracy: 1.0000 - val_loss: 14.3891 - val_accuracy: 0.3153
Epoch 8687/10000
1/1 [==============================] - 0s 102ms/step - loss: 3.1185e-06 - accuracy: 1.0000 - val_loss: 14.3894 - val_accuracy: 0.3153
Epoch 8688/10000
1/1 [==============================] - 0s 112ms/step - loss: 3.1164e-06 - accuracy: 1.0000 - val_loss: 14.3895 - val_accuracy: 0.3153
Epoch 8689/10000
1/1 [==============================] - 0s 103ms/step - loss: 3.1173e-06 - accuracy: 1.0000 - val_loss: 14.3897 - val_accuracy: 0.3154
Epoch 8690/10000
1/1 [==============================] - 0s 104ms/step - loss: 3.1147e-06 - accuracy: 1.0000 - val_loss: 14.3898 - val_accuracy: 0.3154
Epoch 8691/10000
1/1 [==============================] - 0s 104ms/step - loss: 3.1102e-06 - accuracy: 1.0000 - val_loss: 14.3903 - val_accuracy: 0.3154
Epoch 8692/10000
1/1 [==============================] - 0s 105ms/step - loss: 3.1111e-06 - accuracy: 1.0000 - val_loss: 14.3913 - val_accuracy: 0.3154
Epoch 8693/10000
1/1 [==============================] - 0s 103ms/step - loss: 3.1080e-06 - accuracy: 1.0000 - val_loss: 14.3930 - val_accuracy: 0.3154
Epoch 8694/10000
1/1 [==============================] - 0s 103ms/step - loss: 3.1056e-06 - accuracy: 1.0000 - val_loss: 14.3941 - val_accuracy: 0.3154
Epoch 8695/10000
1/1 [==============================] - 0s 104ms/step - loss: 3.1035e-06 - accuracy: 1.0000 - val_loss: 14.3941 - val_accuracy: 0.3153
Epoch 8696/10000
1/1 [==============================] - 0s 107ms/step - loss: 3.1011e-06 - accuracy: 1.0000 - val_loss: 14.3937 - val_accuracy: 0.3154
Epoch 8697/10000
1/1 [==============================] - 0s 114ms/step - loss: 3.1009e-06 - accuracy: 1.0000 - val_loss: 14.3931 - val_accuracy: 0.3154
Epoch 8698/10000
1/1 [==============================] - 0s 104ms/step - loss: 3.0994e-06 - accuracy: 1.0000 - val_loss: 14.3939 - val_accuracy: 0.3154
Epoch 8699/10000
1/1 [==============================] - 0s 105ms/step - loss: 3.0966e-06 - accuracy: 1.0000 - val_loss: 14.3960 - val_accuracy: 0.3154
Epoch 8700/10000
1/1 [==============================] - 0s 108ms/step - loss: 3.0961e-06 - accuracy: 1.0000 - val_loss: 14.3977 - val_accuracy: 0.3154
Epoch 8701/10000
1/1 [==============================] - 0s 110ms/step - loss: 3.0961e-06 - accuracy: 1.0000 - val_loss: 14.3984 - val_accuracy: 0.3153
Epoch 8702/10000
1/1 [==============================] - 0s 107ms/step - loss: 3.0918e-06 - accuracy: 1.0000 - val_loss: 14.3976 - val_accuracy: 0.3153
Epoch 8703/10000
1/1 [==============================] - 0s 104ms/step - loss: 3.0894e-06 - accuracy: 1.0000 - val_loss: 14.3976 - val_accuracy: 0.3154
Epoch 8704/10000
1/1 [==============================] - 0s 103ms/step - loss: 3.0875e-06 - accuracy: 1.0000 - val_loss: 14.3981 - val_accuracy: 0.3154
Epoch 8705/10000
1/1 [==============================] - 0s 103ms/step - loss: 3.0868e-06 - accuracy: 1.0000 - val_loss: 14.3985 - val_accuracy: 0.3155
Epoch 8706/10000
1/1 [==============================] - 0s 102ms/step - loss: 3.0839e-06 - accuracy: 1.0000 - val_loss: 14.3988 - val_accuracy: 0.3154
Epoch 8707/10000
1/1 [==============================] - 0s 102ms/step - loss: 3.0820e-06 - accuracy: 1.0000 - val_loss: 14.3998 - val_accuracy: 0.3154
Epoch 8708/10000
1/1 [==============================] - 0s 101ms/step - loss: 3.0794e-06 - accuracy: 1.0000 - val_loss: 14.4015 - val_accuracy: 0.3154
Epoch 8709/10000
1/1 [==============================] - 0s 101ms/step - loss: 3.0804e-06 - accuracy: 1.0000 - val_loss: 14.4026 - val_accuracy: 0.3153
Epoch 8710/10000
1/1 [==============================] - 0s 104ms/step - loss: 3.0794e-06 - accuracy: 1.0000 - val_loss: 14.4027 - val_accuracy: 0.3153
Epoch 8711/10000
1/1 [==============================] - 0s 110ms/step - loss: 3.0746e-06 - accuracy: 1.0000 - val_loss: 14.4028 - val_accuracy: 0.3153
Epoch 8712/10000
1/1 [==============================] - 0s 106ms/step - loss: 3.0722e-06 - accuracy: 1.0000 - val_loss: 14.4033 - val_accuracy: 0.3152
Epoch 8713/10000
1/1 [==============================] - 0s 108ms/step - loss: 3.0713e-06 - accuracy: 1.0000 - val_loss: 14.4043 - val_accuracy: 0.3153
Epoch 8714/10000
1/1 [==============================] - 0s 110ms/step - loss: 3.0689e-06 - accuracy: 1.0000 - val_loss: 14.4054 - val_accuracy: 0.3154
Epoch 8715/10000
1/1 [==============================] - 0s 102ms/step - loss: 3.0670e-06 - accuracy: 1.0000 - val_loss: 14.4059 - val_accuracy: 0.3154
Epoch 8716/10000
1/1 [==============================] - 0s 109ms/step - loss: 3.0656e-06 - accuracy: 1.0000 - val_loss: 14.4056 - val_accuracy: 0.3154
Epoch 8717/10000
1/1 [==============================] - 0s 104ms/step - loss: 3.0634e-06 - accuracy: 1.0000 - val_loss: 14.4057 - val_accuracy: 0.3154
Epoch 8718/10000
1/1 [==============================] - 0s 102ms/step - loss: 3.0613e-06 - accuracy: 1.0000 - val_loss: 14.4065 - val_accuracy: 0.3154
Epoch 8719/10000
1/1 [==============================] - 0s 105ms/step - loss: 3.0610e-06 - accuracy: 1.0000 - val_loss: 14.4073 - val_accuracy: 0.3153
Epoch 8720/10000
1/1 [==============================] - 0s 101ms/step - loss: 3.0601e-06 - accuracy: 1.0000 - val_loss: 14.4085 - val_accuracy: 0.3154
Epoch 8721/10000
1/1 [==============================] - 0s 99ms/step - loss: 3.0560e-06 - accuracy: 1.0000 - val_loss: 14.4094 - val_accuracy: 0.3154
Epoch 8722/10000
1/1 [==============================] - 0s 104ms/step - loss: 3.0556e-06 - accuracy: 1.0000 - val_loss: 14.4096 - val_accuracy: 0.3153
Epoch 8723/10000
1/1 [==============================] - 0s 102ms/step - loss: 3.0544e-06 - accuracy: 1.0000 - val_loss: 14.4099 - val_accuracy: 0.3153
Epoch 8724/10000
1/1 [==============================] - 0s 103ms/step - loss: 3.0541e-06 - accuracy: 1.0000 - val_loss: 14.4105 - val_accuracy: 0.3153
Epoch 8725/10000
1/1 [==============================] - 0s 102ms/step - loss: 3.0525e-06 - accuracy: 1.0000 - val_loss: 14.4106 - val_accuracy: 0.3154
Epoch 8726/10000
1/1 [==============================] - 0s 103ms/step - loss: 3.0486e-06 - accuracy: 1.0000 - val_loss: 14.4112 - val_accuracy: 0.3153
Epoch 8727/10000
1/1 [==============================] - 0s 100ms/step - loss: 3.0477e-06 - accuracy: 1.0000 - val_loss: 14.4124 - val_accuracy: 0.3153
Epoch 8728/10000
1/1 [==============================] - 0s 103ms/step - loss: 3.0439e-06 - accuracy: 1.0000 - val_loss: 14.4133 - val_accuracy: 0.3154
Epoch 8729/10000
1/1 [==============================] - 0s 101ms/step - loss: 3.0429e-06 - accuracy: 1.0000 - val_loss: 14.4135 - val_accuracy: 0.3154
Epoch 8730/10000
1/1 [==============================] - 0s 104ms/step - loss: 3.0436e-06 - accuracy: 1.0000 - val_loss: 14.4137 - val_accuracy: 0.3153
Epoch 8731/10000
1/1 [==============================] - 0s 107ms/step - loss: 3.0401e-06 - accuracy: 1.0000 - val_loss: 14.4144 - val_accuracy: 0.3152
Epoch 8732/10000
1/1 [==============================] - 0s 103ms/step - loss: 3.0393e-06 - accuracy: 1.0000 - val_loss: 14.4156 - val_accuracy: 0.3153
Epoch 8733/10000
1/1 [==============================] - 0s 102ms/step - loss: 3.0379e-06 - accuracy: 1.0000 - val_loss: 14.4166 - val_accuracy: 0.3153
Epoch 8734/10000
1/1 [==============================] - 0s 108ms/step - loss: 3.0346e-06 - accuracy: 1.0000 - val_loss: 14.4169 - val_accuracy: 0.3153
Epoch 8735/10000
1/1 [==============================] - 0s 105ms/step - loss: 3.0324e-06 - accuracy: 1.0000 - val_loss: 14.4172 - val_accuracy: 0.3154
Epoch 8736/10000
1/1 [==============================] - 0s 111ms/step - loss: 3.0300e-06 - accuracy: 1.0000 - val_loss: 14.4177 - val_accuracy: 0.3154
Epoch 8737/10000
1/1 [==============================] - 0s 106ms/step - loss: 3.0279e-06 - accuracy: 1.0000 - val_loss: 14.4183 - val_accuracy: 0.3153
Epoch 8738/10000
1/1 [==============================] - 0s 104ms/step - loss: 3.0269e-06 - accuracy: 1.0000 - val_loss: 14.4187 - val_accuracy: 0.3154
Epoch 8739/10000
1/1 [==============================] - 0s 108ms/step - loss: 3.0262e-06 - accuracy: 1.0000 - val_loss: 14.4193 - val_accuracy: 0.3154
Epoch 8740/10000
1/1 [==============================] - 0s 106ms/step - loss: 3.0255e-06 - accuracy: 1.0000 - val_loss: 14.4196 - val_accuracy: 0.3154
Epoch 8741/10000
1/1 [==============================] - 0s 112ms/step - loss: 3.0224e-06 - accuracy: 1.0000 - val_loss: 14.4202 - val_accuracy: 0.3153
Epoch 8742/10000
1/1 [==============================] - 0s 107ms/step - loss: 3.0205e-06 - accuracy: 1.0000 - val_loss: 14.4208 - val_accuracy: 0.3152
Epoch 8743/10000
1/1 [==============================] - 0s 105ms/step - loss: 3.0193e-06 - accuracy: 1.0000 - val_loss: 14.4215 - val_accuracy: 0.3152
Epoch 8744/10000
1/1 [==============================] - 0s 109ms/step - loss: 3.0167e-06 - accuracy: 1.0000 - val_loss: 14.4222 - val_accuracy: 0.3153
Epoch 8745/10000
1/1 [==============================] - 0s 115ms/step - loss: 3.0148e-06 - accuracy: 1.0000 - val_loss: 14.4225 - val_accuracy: 0.3153
Epoch 8746/10000
1/1 [==============================] - 0s 103ms/step - loss: 3.0115e-06 - accuracy: 1.0000 - val_loss: 14.4232 - val_accuracy: 0.3153
Epoch 8747/10000
1/1 [==============================] - 0s 107ms/step - loss: 3.0091e-06 - accuracy: 1.0000 - val_loss: 14.4238 - val_accuracy: 0.3154
Epoch 8748/10000
1/1 [==============================] - 0s 113ms/step - loss: 3.0086e-06 - accuracy: 1.0000 - val_loss: 14.4243 - val_accuracy: 0.3154
Epoch 8749/10000
1/1 [==============================] - 0s 108ms/step - loss: 3.0084e-06 - accuracy: 1.0000 - val_loss: 14.4249 - val_accuracy: 0.3154
Epoch 8750/10000
1/1 [==============================] - 0s 104ms/step - loss: 3.0081e-06 - accuracy: 1.0000 - val_loss: 14.4258 - val_accuracy: 0.3153
Epoch 8751/10000
1/1 [==============================] - 0s 108ms/step - loss: 3.0031e-06 - accuracy: 1.0000 - val_loss: 14.4263 - val_accuracy: 0.3153
Epoch 8752/10000
1/1 [==============================] - 0s 105ms/step - loss: 3.0007e-06 - accuracy: 1.0000 - val_loss: 14.4266 - val_accuracy: 0.3152
Epoch 8753/10000
1/1 [==============================] - 0s 108ms/step - loss: 3.0031e-06 - accuracy: 1.0000 - val_loss: 14.4272 - val_accuracy: 0.3152
Epoch 8754/10000
1/1 [==============================] - 0s 99ms/step - loss: 3.0017e-06 - accuracy: 1.0000 - val_loss: 14.4280 - val_accuracy: 0.3153
Epoch 8755/10000
1/1 [==============================] - 0s 104ms/step - loss: 2.9986e-06 - accuracy: 1.0000 - val_loss: 14.4293 - val_accuracy: 0.3153
Epoch 8756/10000
1/1 [==============================] - 0s 103ms/step - loss: 2.9943e-06 - accuracy: 1.0000 - val_loss: 14.4297 - val_accuracy: 0.3153
Epoch 8757/10000
1/1 [==============================] - 0s 102ms/step - loss: 2.9929e-06 - accuracy: 1.0000 - val_loss: 14.4294 - val_accuracy: 0.3153
Epoch 8758/10000
1/1 [==============================] - 0s 106ms/step - loss: 2.9919e-06 - accuracy: 1.0000 - val_loss: 14.4293 - val_accuracy: 0.3153
Epoch 8759/10000
1/1 [==============================] - 0s 102ms/step - loss: 2.9898e-06 - accuracy: 1.0000 - val_loss: 14.4304 - val_accuracy: 0.3153
Epoch 8760/10000
1/1 [==============================] - 0s 102ms/step - loss: 2.9883e-06 - accuracy: 1.0000 - val_loss: 14.4320 - val_accuracy: 0.3153
Epoch 8761/10000
1/1 [==============================] - 0s 102ms/step - loss: 2.9867e-06 - accuracy: 1.0000 - val_loss: 14.4326 - val_accuracy: 0.3152
Epoch 8762/10000
1/1 [==============================] - 0s 101ms/step - loss: 2.9847e-06 - accuracy: 1.0000 - val_loss: 14.4323 - val_accuracy: 0.3152
Epoch 8763/10000
1/1 [==============================] - 0s 109ms/step - loss: 2.9838e-06 - accuracy: 1.0000 - val_loss: 14.4323 - val_accuracy: 0.3153
Epoch 8764/10000
1/1 [==============================] - 0s 105ms/step - loss: 2.9821e-06 - accuracy: 1.0000 - val_loss: 14.4330 - val_accuracy: 0.3152
Epoch 8765/10000
1/1 [==============================] - 0s 106ms/step - loss: 2.9771e-06 - accuracy: 1.0000 - val_loss: 14.4347 - val_accuracy: 0.3153
Epoch 8766/10000
1/1 [==============================] - 0s 106ms/step - loss: 2.9774e-06 - accuracy: 1.0000 - val_loss: 14.4359 - val_accuracy: 0.3154
Epoch 8767/10000
1/1 [==============================] - 0s 105ms/step - loss: 2.9764e-06 - accuracy: 1.0000 - val_loss: 14.4355 - val_accuracy: 0.3153
Epoch 8768/10000
1/1 [==============================] - 0s 104ms/step - loss: 2.9726e-06 - accuracy: 1.0000 - val_loss: 14.4353 - val_accuracy: 0.3152
Epoch 8769/10000
1/1 [==============================] - 0s 103ms/step - loss: 2.9719e-06 - accuracy: 1.0000 - val_loss: 14.4360 - val_accuracy: 0.3152
Epoch 8770/10000
1/1 [==============================] - 0s 101ms/step - loss: 2.9714e-06 - accuracy: 1.0000 - val_loss: 14.4374 - val_accuracy: 0.3152
Epoch 8771/10000
1/1 [==============================] - 0s 102ms/step - loss: 2.9678e-06 - accuracy: 1.0000 - val_loss: 14.4383 - val_accuracy: 0.3153
Epoch 8772/10000
1/1 [==============================] - 0s 104ms/step - loss: 2.9666e-06 - accuracy: 1.0000 - val_loss: 14.4387 - val_accuracy: 0.3153
Epoch 8773/10000
1/1 [==============================] - 0s 108ms/step - loss: 2.9671e-06 - accuracy: 1.0000 - val_loss: 14.4384 - val_accuracy: 0.3153
Epoch 8774/10000
1/1 [==============================] - 0s 120ms/step - loss: 2.9642e-06 - accuracy: 1.0000 - val_loss: 14.4388 - val_accuracy: 0.3154
Epoch 8775/10000
1/1 [==============================] - 0s 109ms/step - loss: 2.9626e-06 - accuracy: 1.0000 - val_loss: 14.4400 - val_accuracy: 0.3154
Epoch 8776/10000
1/1 [==============================] - 0s 108ms/step - loss: 2.9609e-06 - accuracy: 1.0000 - val_loss: 14.4412 - val_accuracy: 0.3153
Epoch 8777/10000
1/1 [==============================] - 0s 103ms/step - loss: 2.9573e-06 - accuracy: 1.0000 - val_loss: 14.4417 - val_accuracy: 0.3153
Epoch 8778/10000
1/1 [==============================] - 0s 107ms/step - loss: 2.9578e-06 - accuracy: 1.0000 - val_loss: 14.4419 - val_accuracy: 0.3153
Epoch 8779/10000
1/1 [==============================] - 0s 108ms/step - loss: 2.9545e-06 - accuracy: 1.0000 - val_loss: 14.4419 - val_accuracy: 0.3154
Epoch 8780/10000
1/1 [==============================] - 0s 103ms/step - loss: 2.9533e-06 - accuracy: 1.0000 - val_loss: 14.4421 - val_accuracy: 0.3153
Epoch 8781/10000
1/1 [==============================] - 0s 102ms/step - loss: 2.9521e-06 - accuracy: 1.0000 - val_loss: 14.4431 - val_accuracy: 0.3153
Epoch 8782/10000
1/1 [==============================] - 0s 104ms/step - loss: 2.9492e-06 - accuracy: 1.0000 - val_loss: 14.4443 - val_accuracy: 0.3153
Epoch 8783/10000
1/1 [==============================] - 0s 108ms/step - loss: 2.9478e-06 - accuracy: 1.0000 - val_loss: 14.4452 - val_accuracy: 0.3153
Epoch 8784/10000
1/1 [==============================] - 0s 100ms/step - loss: 2.9468e-06 - accuracy: 1.0000 - val_loss: 14.4454 - val_accuracy: 0.3154
Epoch 8785/10000
1/1 [==============================] - 0s 104ms/step - loss: 2.9442e-06 - accuracy: 1.0000 - val_loss: 14.4456 - val_accuracy: 0.3154
Epoch 8786/10000
1/1 [==============================] - 0s 104ms/step - loss: 2.9411e-06 - accuracy: 1.0000 - val_loss: 14.4464 - val_accuracy: 0.3152
Epoch 8787/10000
1/1 [==============================] - 0s 104ms/step - loss: 2.9394e-06 - accuracy: 1.0000 - val_loss: 14.4475 - val_accuracy: 0.3153
Epoch 8788/10000
1/1 [==============================] - 0s 109ms/step - loss: 2.9371e-06 - accuracy: 1.0000 - val_loss: 14.4480 - val_accuracy: 0.3153
Epoch 8789/10000
1/1 [==============================] - 0s 108ms/step - loss: 2.9366e-06 - accuracy: 1.0000 - val_loss: 14.4481 - val_accuracy: 0.3154
Epoch 8790/10000
1/1 [==============================] - 0s 104ms/step - loss: 2.9356e-06 - accuracy: 1.0000 - val_loss: 14.4486 - val_accuracy: 0.3154
Epoch 8791/10000
1/1 [==============================] - 0s 109ms/step - loss: 2.9335e-06 - accuracy: 1.0000 - val_loss: 14.4493 - val_accuracy: 0.3153
Epoch 8792/10000
1/1 [==============================] - 0s 107ms/step - loss: 2.9318e-06 - accuracy: 1.0000 - val_loss: 14.4502 - val_accuracy: 0.3153
Epoch 8793/10000
1/1 [==============================] - 0s 105ms/step - loss: 2.9299e-06 - accuracy: 1.0000 - val_loss: 14.4510 - val_accuracy: 0.3152
Epoch 8794/10000
1/1 [==============================] - 0s 103ms/step - loss: 2.9302e-06 - accuracy: 1.0000 - val_loss: 14.4515 - val_accuracy: 0.3154
Epoch 8795/10000
1/1 [==============================] - 0s 113ms/step - loss: 2.9278e-06 - accuracy: 1.0000 - val_loss: 14.4518 - val_accuracy: 0.3153
Epoch 8796/10000
1/1 [==============================] - 0s 104ms/step - loss: 2.9230e-06 - accuracy: 1.0000 - val_loss: 14.4520 - val_accuracy: 0.3152
Epoch 8797/10000
1/1 [==============================] - 0s 104ms/step - loss: 2.9216e-06 - accuracy: 1.0000 - val_loss: 14.4522 - val_accuracy: 0.3153
Epoch 8798/10000
1/1 [==============================] - 0s 105ms/step - loss: 2.9213e-06 - accuracy: 1.0000 - val_loss: 14.4528 - val_accuracy: 0.3153
Epoch 8799/10000
1/1 [==============================] - 0s 108ms/step - loss: 2.9199e-06 - accuracy: 1.0000 - val_loss: 14.4543 - val_accuracy: 0.3153
Epoch 8800/10000
1/1 [==============================] - 0s 110ms/step - loss: 2.9194e-06 - accuracy: 1.0000 - val_loss: 14.4552 - val_accuracy: 0.3152
Epoch 8801/10000
1/1 [==============================] - 0s 108ms/step - loss: 2.9182e-06 - accuracy: 1.0000 - val_loss: 14.4553 - val_accuracy: 0.3152
Epoch 8802/10000
1/1 [==============================] - 0s 108ms/step - loss: 2.9151e-06 - accuracy: 1.0000 - val_loss: 14.4550 - val_accuracy: 0.3153
Epoch 8803/10000
1/1 [==============================] - 0s 111ms/step - loss: 2.9130e-06 - accuracy: 1.0000 - val_loss: 14.4558 - val_accuracy: 0.3154
Epoch 8804/10000
1/1 [==============================] - 0s 116ms/step - loss: 2.9116e-06 - accuracy: 1.0000 - val_loss: 14.4569 - val_accuracy: 0.3155
Epoch 8805/10000
1/1 [==============================] - 0s 105ms/step - loss: 2.9099e-06 - accuracy: 1.0000 - val_loss: 14.4580 - val_accuracy: 0.3154
Epoch 8806/10000
1/1 [==============================] - 0s 110ms/step - loss: 2.9073e-06 - accuracy: 1.0000 - val_loss: 14.4583 - val_accuracy: 0.3153
Epoch 8807/10000
1/1 [==============================] - 0s 106ms/step - loss: 2.9077e-06 - accuracy: 1.0000 - val_loss: 14.4586 - val_accuracy: 0.3152
Epoch 8808/10000
1/1 [==============================] - 0s 109ms/step - loss: 2.9042e-06 - accuracy: 1.0000 - val_loss: 14.4585 - val_accuracy: 0.3152
Epoch 8809/10000
1/1 [==============================] - 0s 114ms/step - loss: 2.9042e-06 - accuracy: 1.0000 - val_loss: 14.4590 - val_accuracy: 0.3151
Epoch 8810/10000
1/1 [==============================] - 0s 116ms/step - loss: 2.9025e-06 - accuracy: 1.0000 - val_loss: 14.4595 - val_accuracy: 0.3156
Epoch 8811/10000
1/1 [==============================] - 0s 124ms/step - loss: 2.8999e-06 - accuracy: 1.0000 - val_loss: 14.4598 - val_accuracy: 0.3155
Epoch 8812/10000
1/1 [==============================] - 0s 115ms/step - loss: 2.8982e-06 - accuracy: 1.0000 - val_loss: 14.4605 - val_accuracy: 0.3154
Epoch 8813/10000
1/1 [==============================] - 0s 115ms/step - loss: 2.8956e-06 - accuracy: 1.0000 - val_loss: 14.4618 - val_accuracy: 0.3155
Epoch 8814/10000
1/1 [==============================] - 0s 114ms/step - loss: 2.8915e-06 - accuracy: 1.0000 - val_loss: 14.4632 - val_accuracy: 0.3155
Epoch 8815/10000
1/1 [==============================] - 0s 114ms/step - loss: 2.8920e-06 - accuracy: 1.0000 - val_loss: 14.4633 - val_accuracy: 0.3154
Epoch 8816/10000
1/1 [==============================] - 0s 107ms/step - loss: 2.8932e-06 - accuracy: 1.0000 - val_loss: 14.4632 - val_accuracy: 0.3151
Epoch 8817/10000
1/1 [==============================] - 0s 105ms/step - loss: 2.8911e-06 - accuracy: 1.0000 - val_loss: 14.4631 - val_accuracy: 0.3154
Epoch 8818/10000
1/1 [==============================] - 0s 102ms/step - loss: 2.8887e-06 - accuracy: 1.0000 - val_loss: 14.4636 - val_accuracy: 0.3153
Epoch 8819/10000
1/1 [==============================] - 0s 102ms/step - loss: 2.8846e-06 - accuracy: 1.0000 - val_loss: 14.4648 - val_accuracy: 0.3154
Epoch 8820/10000
1/1 [==============================] - 0s 102ms/step - loss: 2.8832e-06 - accuracy: 1.0000 - val_loss: 14.4655 - val_accuracy: 0.3154
Epoch 8821/10000
1/1 [==============================] - 0s 110ms/step - loss: 2.8825e-06 - accuracy: 1.0000 - val_loss: 14.4663 - val_accuracy: 0.3153
Epoch 8822/10000
1/1 [==============================] - 0s 102ms/step - loss: 2.8806e-06 - accuracy: 1.0000 - val_loss: 14.4671 - val_accuracy: 0.3154
Epoch 8823/10000
1/1 [==============================] - 0s 103ms/step - loss: 2.8760e-06 - accuracy: 1.0000 - val_loss: 14.4679 - val_accuracy: 0.3154
Epoch 8824/10000
1/1 [==============================] - 0s 102ms/step - loss: 2.8770e-06 - accuracy: 1.0000 - val_loss: 14.4684 - val_accuracy: 0.3152
Epoch 8825/10000
1/1 [==============================] - 0s 103ms/step - loss: 2.8760e-06 - accuracy: 1.0000 - val_loss: 14.4685 - val_accuracy: 0.3153
Epoch 8826/10000
1/1 [==============================] - 0s 104ms/step - loss: 2.8725e-06 - accuracy: 1.0000 - val_loss: 14.4695 - val_accuracy: 0.3153
Epoch 8827/10000
1/1 [==============================] - 0s 104ms/step - loss: 2.8703e-06 - accuracy: 1.0000 - val_loss: 14.4711 - val_accuracy: 0.3155
Epoch 8828/10000
1/1 [==============================] - 0s 102ms/step - loss: 2.8708e-06 - accuracy: 1.0000 - val_loss: 14.4712 - val_accuracy: 0.3155
Epoch 8829/10000
1/1 [==============================] - 0s 104ms/step - loss: 2.8660e-06 - accuracy: 1.0000 - val_loss: 14.4708 - val_accuracy: 0.3153
Epoch 8830/10000
1/1 [==============================] - 0s 107ms/step - loss: 2.8674e-06 - accuracy: 1.0000 - val_loss: 14.4709 - val_accuracy: 0.3153
Epoch 8831/10000
1/1 [==============================] - 0s 107ms/step - loss: 2.8665e-06 - accuracy: 1.0000 - val_loss: 14.4722 - val_accuracy: 0.3154
Epoch 8832/10000
1/1 [==============================] - 0s 102ms/step - loss: 2.8624e-06 - accuracy: 1.0000 - val_loss: 14.4739 - val_accuracy: 0.3154
Epoch 8833/10000
1/1 [==============================] - 0s 106ms/step - loss: 2.8598e-06 - accuracy: 1.0000 - val_loss: 14.4740 - val_accuracy: 0.3154
Epoch 8834/10000
1/1 [==============================] - 0s 194ms/step - loss: 2.8596e-06 - accuracy: 1.0000 - val_loss: 14.4736 - val_accuracy: 0.3153
Epoch 8835/10000
1/1 [==============================] - 0s 246ms/step - loss: 2.8560e-06 - accuracy: 1.0000 - val_loss: 14.4743 - val_accuracy: 0.3153
Epoch 8836/10000
1/1 [==============================] - 0s 243ms/step - loss: 2.8572e-06 - accuracy: 1.0000 - val_loss: 14.4754 - val_accuracy: 0.3154
Epoch 8837/10000
1/1 [==============================] - 0s 227ms/step - loss: 2.8531e-06 - accuracy: 1.0000 - val_loss: 14.4762 - val_accuracy: 0.3154
Epoch 8838/10000
1/1 [==============================] - 0s 109ms/step - loss: 2.8529e-06 - accuracy: 1.0000 - val_loss: 14.4767 - val_accuracy: 0.3153
Epoch 8839/10000
1/1 [==============================] - 0s 105ms/step - loss: 2.8536e-06 - accuracy: 1.0000 - val_loss: 14.4771 - val_accuracy: 0.3153
Epoch 8840/10000
1/1 [==============================] - 0s 106ms/step - loss: 2.8508e-06 - accuracy: 1.0000 - val_loss: 14.4777 - val_accuracy: 0.3154
Epoch 8841/10000
1/1 [==============================] - 0s 104ms/step - loss: 2.8458e-06 - accuracy: 1.0000 - val_loss: 14.4782 - val_accuracy: 0.3154
Epoch 8842/10000
1/1 [==============================] - 0s 109ms/step - loss: 2.8465e-06 - accuracy: 1.0000 - val_loss: 14.4791 - val_accuracy: 0.3154
Epoch 8843/10000
1/1 [==============================] - 0s 113ms/step - loss: 2.8434e-06 - accuracy: 1.0000 - val_loss: 14.4798 - val_accuracy: 0.3154
Epoch 8844/10000
1/1 [==============================] - 0s 112ms/step - loss: 2.8419e-06 - accuracy: 1.0000 - val_loss: 14.4796 - val_accuracy: 0.3152
Epoch 8845/10000
1/1 [==============================] - 0s 108ms/step - loss: 2.8403e-06 - accuracy: 1.0000 - val_loss: 14.4797 - val_accuracy: 0.3151
Epoch 8846/10000
1/1 [==============================] - 0s 108ms/step - loss: 2.8388e-06 - accuracy: 1.0000 - val_loss: 14.4801 - val_accuracy: 0.3152
Epoch 8847/10000
1/1 [==============================] - 0s 111ms/step - loss: 2.8367e-06 - accuracy: 1.0000 - val_loss: 14.4809 - val_accuracy: 0.3153
Epoch 8848/10000
1/1 [==============================] - 0s 106ms/step - loss: 2.8350e-06 - accuracy: 1.0000 - val_loss: 14.4826 - val_accuracy: 0.3154
Epoch 8849/10000
1/1 [==============================] - 0s 107ms/step - loss: 2.8334e-06 - accuracy: 1.0000 - val_loss: 14.4832 - val_accuracy: 0.3155
Epoch 8850/10000
1/1 [==============================] - 0s 114ms/step - loss: 2.8317e-06 - accuracy: 1.0000 - val_loss: 14.4831 - val_accuracy: 0.3154
Epoch 8851/10000
1/1 [==============================] - 0s 106ms/step - loss: 2.8288e-06 - accuracy: 1.0000 - val_loss: 14.4834 - val_accuracy: 0.3152
Epoch 8852/10000
1/1 [==============================] - 0s 104ms/step - loss: 2.8272e-06 - accuracy: 1.0000 - val_loss: 14.4846 - val_accuracy: 0.3153
Epoch 8853/10000
1/1 [==============================] - 0s 105ms/step - loss: 2.8257e-06 - accuracy: 1.0000 - val_loss: 14.4856 - val_accuracy: 0.3153
Epoch 8854/10000
1/1 [==============================] - 0s 109ms/step - loss: 2.8245e-06 - accuracy: 1.0000 - val_loss: 14.4857 - val_accuracy: 0.3154
Epoch 8855/10000
1/1 [==============================] - 0s 107ms/step - loss: 2.8231e-06 - accuracy: 1.0000 - val_loss: 14.4860 - val_accuracy: 0.3154
Epoch 8856/10000
1/1 [==============================] - 0s 110ms/step - loss: 2.8221e-06 - accuracy: 1.0000 - val_loss: 14.4870 - val_accuracy: 0.3154
Epoch 8857/10000
1/1 [==============================] - 0s 103ms/step - loss: 2.8210e-06 - accuracy: 1.0000 - val_loss: 14.4878 - val_accuracy: 0.3154
Epoch 8858/10000
1/1 [==============================] - 0s 107ms/step - loss: 2.8176e-06 - accuracy: 1.0000 - val_loss: 14.4879 - val_accuracy: 0.3154
Epoch 8859/10000
1/1 [==============================] - 0s 104ms/step - loss: 2.8160e-06 - accuracy: 1.0000 - val_loss: 14.4885 - val_accuracy: 0.3154
Epoch 8860/10000
1/1 [==============================] - 0s 110ms/step - loss: 2.8145e-06 - accuracy: 1.0000 - val_loss: 14.4895 - val_accuracy: 0.3153
Epoch 8861/10000
1/1 [==============================] - 0s 109ms/step - loss: 2.8117e-06 - accuracy: 1.0000 - val_loss: 14.4902 - val_accuracy: 0.3153
Epoch 8862/10000
1/1 [==============================] - 0s 113ms/step - loss: 2.8098e-06 - accuracy: 1.0000 - val_loss: 14.4907 - val_accuracy: 0.3153
Epoch 8863/10000
1/1 [==============================] - 0s 110ms/step - loss: 2.8090e-06 - accuracy: 1.0000 - val_loss: 14.4908 - val_accuracy: 0.3153
Epoch 8864/10000
1/1 [==============================] - 0s 107ms/step - loss: 2.8074e-06 - accuracy: 1.0000 - val_loss: 14.4914 - val_accuracy: 0.3153
Epoch 8865/10000
1/1 [==============================] - 0s 110ms/step - loss: 2.8059e-06 - accuracy: 1.0000 - val_loss: 14.4918 - val_accuracy: 0.3152
Epoch 8866/10000
1/1 [==============================] - 0s 116ms/step - loss: 2.8043e-06 - accuracy: 1.0000 - val_loss: 14.4930 - val_accuracy: 0.3154
Epoch 8867/10000
1/1 [==============================] - 0s 112ms/step - loss: 2.8047e-06 - accuracy: 1.0000 - val_loss: 14.4930 - val_accuracy: 0.3154
Epoch 8868/10000
1/1 [==============================] - 0s 107ms/step - loss: 2.8009e-06 - accuracy: 1.0000 - val_loss: 14.4931 - val_accuracy: 0.3153
Epoch 8869/10000
1/1 [==============================] - 0s 104ms/step - loss: 2.7993e-06 - accuracy: 1.0000 - val_loss: 14.4936 - val_accuracy: 0.3152
Epoch 8870/10000
1/1 [==============================] - 0s 107ms/step - loss: 2.7983e-06 - accuracy: 1.0000 - val_loss: 14.4948 - val_accuracy: 0.3152
Epoch 8871/10000
1/1 [==============================] - 0s 102ms/step - loss: 2.7985e-06 - accuracy: 1.0000 - val_loss: 14.4956 - val_accuracy: 0.3153
Epoch 8872/10000
1/1 [==============================] - 0s 103ms/step - loss: 2.7952e-06 - accuracy: 1.0000 - val_loss: 14.4968 - val_accuracy: 0.3154
Epoch 8873/10000
1/1 [==============================] - 0s 106ms/step - loss: 2.7952e-06 - accuracy: 1.0000 - val_loss: 14.4971 - val_accuracy: 0.3154
Epoch 8874/10000
1/1 [==============================] - 0s 108ms/step - loss: 2.7904e-06 - accuracy: 1.0000 - val_loss: 14.4968 - val_accuracy: 0.3152
Epoch 8875/10000
1/1 [==============================] - 0s 98ms/step - loss: 2.7900e-06 - accuracy: 1.0000 - val_loss: 14.4967 - val_accuracy: 0.3152
Epoch 8876/10000
1/1 [==============================] - 0s 101ms/step - loss: 2.7876e-06 - accuracy: 1.0000 - val_loss: 14.4976 - val_accuracy: 0.3152
Epoch 8877/10000
1/1 [==============================] - 0s 108ms/step - loss: 2.7859e-06 - accuracy: 1.0000 - val_loss: 14.4992 - val_accuracy: 0.3153
Epoch 8878/10000
1/1 [==============================] - 0s 100ms/step - loss: 2.7861e-06 - accuracy: 1.0000 - val_loss: 14.4998 - val_accuracy: 0.3153
Epoch 8879/10000
1/1 [==============================] - 0s 103ms/step - loss: 2.7842e-06 - accuracy: 1.0000 - val_loss: 14.5004 - val_accuracy: 0.3155
Epoch 8880/10000
1/1 [==============================] - 0s 103ms/step - loss: 2.7809e-06 - accuracy: 1.0000 - val_loss: 14.5005 - val_accuracy: 0.3154
Epoch 8881/10000
1/1 [==============================] - 0s 103ms/step - loss: 2.7811e-06 - accuracy: 1.0000 - val_loss: 14.5009 - val_accuracy: 0.3154
Epoch 8882/10000
1/1 [==============================] - 0s 99ms/step - loss: 2.7792e-06 - accuracy: 1.0000 - val_loss: 14.5016 - val_accuracy: 0.3153
Epoch 8883/10000
1/1 [==============================] - 0s 99ms/step - loss: 2.7761e-06 - accuracy: 1.0000 - val_loss: 14.5032 - val_accuracy: 0.3155
Epoch 8884/10000
1/1 [==============================] - 0s 101ms/step - loss: 2.7752e-06 - accuracy: 1.0000 - val_loss: 14.5036 - val_accuracy: 0.3153
Epoch 8885/10000
1/1 [==============================] - 0s 104ms/step - loss: 2.7728e-06 - accuracy: 1.0000 - val_loss: 14.5033 - val_accuracy: 0.3153
Epoch 8886/10000
1/1 [==============================] - 0s 99ms/step - loss: 2.7711e-06 - accuracy: 1.0000 - val_loss: 14.5037 - val_accuracy: 0.3152
Epoch 8887/10000
1/1 [==============================] - 0s 101ms/step - loss: 2.7707e-06 - accuracy: 1.0000 - val_loss: 14.5047 - val_accuracy: 0.3153
Epoch 8888/10000
1/1 [==============================] - 0s 102ms/step - loss: 2.7673e-06 - accuracy: 1.0000 - val_loss: 14.5056 - val_accuracy: 0.3153
Epoch 8889/10000
1/1 [==============================] - 0s 101ms/step - loss: 2.7645e-06 - accuracy: 1.0000 - val_loss: 14.5063 - val_accuracy: 0.3153
Epoch 8890/10000
1/1 [==============================] - 0s 102ms/step - loss: 2.7633e-06 - accuracy: 1.0000 - val_loss: 14.5069 - val_accuracy: 0.3153
Epoch 8891/10000
1/1 [==============================] - 0s 101ms/step - loss: 2.7594e-06 - accuracy: 1.0000 - val_loss: 14.5068 - val_accuracy: 0.3152
Epoch 8892/10000
1/1 [==============================] - 0s 107ms/step - loss: 2.7611e-06 - accuracy: 1.0000 - val_loss: 14.5073 - val_accuracy: 0.3152
Epoch 8893/10000
1/1 [==============================] - 0s 103ms/step - loss: 2.7585e-06 - accuracy: 1.0000 - val_loss: 14.5073 - val_accuracy: 0.3153
Epoch 8894/10000
1/1 [==============================] - 0s 106ms/step - loss: 2.7590e-06 - accuracy: 1.0000 - val_loss: 14.5073 - val_accuracy: 0.3153
Epoch 8895/10000
1/1 [==============================] - 0s 104ms/step - loss: 2.7578e-06 - accuracy: 1.0000 - val_loss: 14.5081 - val_accuracy: 0.3153
Epoch 8896/10000
1/1 [==============================] - 0s 103ms/step - loss: 2.7563e-06 - accuracy: 1.0000 - val_loss: 14.5096 - val_accuracy: 0.3153
Epoch 8897/10000
1/1 [==============================] - 0s 106ms/step - loss: 2.7537e-06 - accuracy: 1.0000 - val_loss: 14.5110 - val_accuracy: 0.3152
Epoch 8898/10000
1/1 [==============================] - 0s 103ms/step - loss: 2.7506e-06 - accuracy: 1.0000 - val_loss: 14.5113 - val_accuracy: 0.3153
Epoch 8899/10000
1/1 [==============================] - 0s 102ms/step - loss: 2.7485e-06 - accuracy: 1.0000 - val_loss: 14.5114 - val_accuracy: 0.3153
Epoch 8900/10000
1/1 [==============================] - 0s 101ms/step - loss: 2.7470e-06 - accuracy: 1.0000 - val_loss: 14.5121 - val_accuracy: 0.3153
Epoch 8901/10000
1/1 [==============================] - 0s 114ms/step - loss: 2.7475e-06 - accuracy: 1.0000 - val_loss: 14.5135 - val_accuracy: 0.3154
Epoch 8902/10000
1/1 [==============================] - 0s 111ms/step - loss: 2.7451e-06 - accuracy: 1.0000 - val_loss: 14.5142 - val_accuracy: 0.3154
Epoch 8903/10000
1/1 [==============================] - 0s 105ms/step - loss: 2.7435e-06 - accuracy: 1.0000 - val_loss: 14.5144 - val_accuracy: 0.3153
Epoch 8904/10000
1/1 [==============================] - 0s 102ms/step - loss: 2.7439e-06 - accuracy: 1.0000 - val_loss: 14.5146 - val_accuracy: 0.3153
Epoch 8905/10000
1/1 [==============================] - 0s 112ms/step - loss: 2.7416e-06 - accuracy: 1.0000 - val_loss: 14.5153 - val_accuracy: 0.3152
Epoch 8906/10000
1/1 [==============================] - 0s 114ms/step - loss: 2.7406e-06 - accuracy: 1.0000 - val_loss: 14.5160 - val_accuracy: 0.3152
Epoch 8907/10000
1/1 [==============================] - 0s 118ms/step - loss: 2.7380e-06 - accuracy: 1.0000 - val_loss: 14.5166 - val_accuracy: 0.3154
Epoch 8908/10000
1/1 [==============================] - 0s 112ms/step - loss: 2.7380e-06 - accuracy: 1.0000 - val_loss: 14.5168 - val_accuracy: 0.3153
Epoch 8909/10000
1/1 [==============================] - 0s 109ms/step - loss: 2.7358e-06 - accuracy: 1.0000 - val_loss: 14.5176 - val_accuracy: 0.3153
Epoch 8910/10000
1/1 [==============================] - 0s 103ms/step - loss: 2.7337e-06 - accuracy: 1.0000 - val_loss: 14.5182 - val_accuracy: 0.3153
Epoch 8911/10000
1/1 [==============================] - 0s 102ms/step - loss: 2.7323e-06 - accuracy: 1.0000 - val_loss: 14.5185 - val_accuracy: 0.3151
Epoch 8912/10000
1/1 [==============================] - 0s 105ms/step - loss: 2.7316e-06 - accuracy: 1.0000 - val_loss: 14.5183 - val_accuracy: 0.3152
Epoch 8913/10000
1/1 [==============================] - 0s 117ms/step - loss: 2.7308e-06 - accuracy: 1.0000 - val_loss: 14.5191 - val_accuracy: 0.3152
Epoch 8914/10000
1/1 [==============================] - 0s 105ms/step - loss: 2.7275e-06 - accuracy: 1.0000 - val_loss: 14.5208 - val_accuracy: 0.3152
Epoch 8915/10000
1/1 [==============================] - 0s 108ms/step - loss: 2.7254e-06 - accuracy: 1.0000 - val_loss: 14.5213 - val_accuracy: 0.3152
Epoch 8916/10000
1/1 [==============================] - 0s 102ms/step - loss: 2.7242e-06 - accuracy: 1.0000 - val_loss: 14.5214 - val_accuracy: 0.3152
Epoch 8917/10000
1/1 [==============================] - 0s 104ms/step - loss: 2.7232e-06 - accuracy: 1.0000 - val_loss: 14.5212 - val_accuracy: 0.3152
Epoch 8918/10000
1/1 [==============================] - 0s 114ms/step - loss: 2.7208e-06 - accuracy: 1.0000 - val_loss: 14.5220 - val_accuracy: 0.3152
Epoch 8919/10000
1/1 [==============================] - 0s 107ms/step - loss: 2.7194e-06 - accuracy: 1.0000 - val_loss: 14.5240 - val_accuracy: 0.3154
Epoch 8920/10000
1/1 [==============================] - 0s 106ms/step - loss: 2.7194e-06 - accuracy: 1.0000 - val_loss: 14.5250 - val_accuracy: 0.3155
Epoch 8921/10000
1/1 [==============================] - 0s 110ms/step - loss: 2.7182e-06 - accuracy: 1.0000 - val_loss: 14.5248 - val_accuracy: 0.3154
Epoch 8922/10000
1/1 [==============================] - 0s 104ms/step - loss: 2.7156e-06 - accuracy: 1.0000 - val_loss: 14.5236 - val_accuracy: 0.3153
Epoch 8923/10000
1/1 [==============================] - 0s 112ms/step - loss: 2.7137e-06 - accuracy: 1.0000 - val_loss: 14.5238 - val_accuracy: 0.3152
Epoch 8924/10000
1/1 [==============================] - 0s 107ms/step - loss: 2.7122e-06 - accuracy: 1.0000 - val_loss: 14.5256 - val_accuracy: 0.3152
Epoch 8925/10000
1/1 [==============================] - 0s 102ms/step - loss: 2.7110e-06 - accuracy: 1.0000 - val_loss: 14.5279 - val_accuracy: 0.3155
Epoch 8926/10000
1/1 [==============================] - 0s 108ms/step - loss: 2.7115e-06 - accuracy: 1.0000 - val_loss: 14.5290 - val_accuracy: 0.3155
Epoch 8927/10000
1/1 [==============================] - 0s 111ms/step - loss: 2.7079e-06 - accuracy: 1.0000 - val_loss: 14.5287 - val_accuracy: 0.3155
Epoch 8928/10000
1/1 [==============================] - 0s 105ms/step - loss: 2.7056e-06 - accuracy: 1.0000 - val_loss: 14.5277 - val_accuracy: 0.3151
Epoch 8929/10000
1/1 [==============================] - 0s 105ms/step - loss: 2.7048e-06 - accuracy: 1.0000 - val_loss: 14.5282 - val_accuracy: 0.3152
Epoch 8930/10000
1/1 [==============================] - 0s 105ms/step - loss: 2.7032e-06 - accuracy: 1.0000 - val_loss: 14.5299 - val_accuracy: 0.3153
Epoch 8931/10000
1/1 [==============================] - 0s 104ms/step - loss: 2.6996e-06 - accuracy: 1.0000 - val_loss: 14.5315 - val_accuracy: 0.3154
Epoch 8932/10000
1/1 [==============================] - 0s 102ms/step - loss: 2.7001e-06 - accuracy: 1.0000 - val_loss: 14.5318 - val_accuracy: 0.3153
Epoch 8933/10000
1/1 [==============================] - 0s 101ms/step - loss: 2.6984e-06 - accuracy: 1.0000 - val_loss: 14.5314 - val_accuracy: 0.3153
Epoch 8934/10000
1/1 [==============================] - 0s 100ms/step - loss: 2.6955e-06 - accuracy: 1.0000 - val_loss: 14.5315 - val_accuracy: 0.3152
Epoch 8935/10000
1/1 [==============================] - 0s 101ms/step - loss: 2.6934e-06 - accuracy: 1.0000 - val_loss: 14.5323 - val_accuracy: 0.3154
Epoch 8936/10000
1/1 [==============================] - 0s 103ms/step - loss: 2.6929e-06 - accuracy: 1.0000 - val_loss: 14.5335 - val_accuracy: 0.3154
Epoch 8937/10000
1/1 [==============================] - 0s 105ms/step - loss: 2.6948e-06 - accuracy: 1.0000 - val_loss: 14.5343 - val_accuracy: 0.3154
Epoch 8938/10000
1/1 [==============================] - 0s 99ms/step - loss: 2.6903e-06 - accuracy: 1.0000 - val_loss: 14.5344 - val_accuracy: 0.3152
Epoch 8939/10000
1/1 [==============================] - 0s 100ms/step - loss: 2.6874e-06 - accuracy: 1.0000 - val_loss: 14.5348 - val_accuracy: 0.3153
Epoch 8940/10000
1/1 [==============================] - 0s 110ms/step - loss: 2.6867e-06 - accuracy: 1.0000 - val_loss: 14.5354 - val_accuracy: 0.3154
Epoch 8941/10000
1/1 [==============================] - 0s 109ms/step - loss: 2.6851e-06 - accuracy: 1.0000 - val_loss: 14.5359 - val_accuracy: 0.3153
Epoch 8942/10000
1/1 [==============================] - 0s 110ms/step - loss: 2.6836e-06 - accuracy: 1.0000 - val_loss: 14.5365 - val_accuracy: 0.3153
Epoch 8943/10000
1/1 [==============================] - 0s 108ms/step - loss: 2.6832e-06 - accuracy: 1.0000 - val_loss: 14.5375 - val_accuracy: 0.3153
Epoch 8944/10000
1/1 [==============================] - 0s 108ms/step - loss: 2.6820e-06 - accuracy: 1.0000 - val_loss: 14.5382 - val_accuracy: 0.3154
Epoch 8945/10000
1/1 [==============================] - 0s 104ms/step - loss: 2.6803e-06 - accuracy: 1.0000 - val_loss: 14.5388 - val_accuracy: 0.3154
Epoch 8946/10000
1/1 [==============================] - 0s 104ms/step - loss: 2.6762e-06 - accuracy: 1.0000 - val_loss: 14.5385 - val_accuracy: 0.3154
Epoch 8947/10000
1/1 [==============================] - 0s 104ms/step - loss: 2.6765e-06 - accuracy: 1.0000 - val_loss: 14.5384 - val_accuracy: 0.3152
Epoch 8948/10000
1/1 [==============================] - 0s 104ms/step - loss: 2.6748e-06 - accuracy: 1.0000 - val_loss: 14.5390 - val_accuracy: 0.3153
Epoch 8949/10000
1/1 [==============================] - 0s 106ms/step - loss: 2.6724e-06 - accuracy: 1.0000 - val_loss: 14.5398 - val_accuracy: 0.3152
Epoch 8950/10000
1/1 [==============================] - 0s 101ms/step - loss: 2.6717e-06 - accuracy: 1.0000 - val_loss: 14.5408 - val_accuracy: 0.3154
Epoch 8951/10000
1/1 [==============================] - 0s 105ms/step - loss: 2.6691e-06 - accuracy: 1.0000 - val_loss: 14.5419 - val_accuracy: 0.3153
Epoch 8952/10000
1/1 [==============================] - 0s 103ms/step - loss: 2.6657e-06 - accuracy: 1.0000 - val_loss: 14.5435 - val_accuracy: 0.3154
Epoch 8953/10000
1/1 [==============================] - 0s 104ms/step - loss: 2.6650e-06 - accuracy: 1.0000 - val_loss: 14.5434 - val_accuracy: 0.3154
Epoch 8954/10000
1/1 [==============================] - 0s 109ms/step - loss: 2.6636e-06 - accuracy: 1.0000 - val_loss: 14.5429 - val_accuracy: 0.3152
Epoch 8955/10000
1/1 [==============================] - 0s 102ms/step - loss: 2.6638e-06 - accuracy: 1.0000 - val_loss: 14.5433 - val_accuracy: 0.3153
Epoch 8956/10000
1/1 [==============================] - 0s 100ms/step - loss: 2.6626e-06 - accuracy: 1.0000 - val_loss: 14.5446 - val_accuracy: 0.3155
Epoch 8957/10000
1/1 [==============================] - 0s 105ms/step - loss: 2.6593e-06 - accuracy: 1.0000 - val_loss: 14.5452 - val_accuracy: 0.3153
Epoch 8958/10000
1/1 [==============================] - 0s 109ms/step - loss: 2.6579e-06 - accuracy: 1.0000 - val_loss: 14.5460 - val_accuracy: 0.3154
Epoch 8959/10000
1/1 [==============================] - 0s 104ms/step - loss: 2.6557e-06 - accuracy: 1.0000 - val_loss: 14.5469 - val_accuracy: 0.3154
Epoch 8960/10000
1/1 [==============================] - 0s 103ms/step - loss: 2.6557e-06 - accuracy: 1.0000 - val_loss: 14.5470 - val_accuracy: 0.3154
Epoch 8961/10000
1/1 [==============================] - 0s 105ms/step - loss: 2.6538e-06 - accuracy: 1.0000 - val_loss: 14.5467 - val_accuracy: 0.3152
Epoch 8962/10000
1/1 [==============================] - 0s 107ms/step - loss: 2.6514e-06 - accuracy: 1.0000 - val_loss: 14.5476 - val_accuracy: 0.3153
Epoch 8963/10000
1/1 [==============================] - 0s 111ms/step - loss: 2.6503e-06 - accuracy: 1.0000 - val_loss: 14.5490 - val_accuracy: 0.3153
Epoch 8964/10000
1/1 [==============================] - 0s 104ms/step - loss: 2.6486e-06 - accuracy: 1.0000 - val_loss: 14.5498 - val_accuracy: 0.3153
Epoch 8965/10000
1/1 [==============================] - 0s 105ms/step - loss: 2.6495e-06 - accuracy: 1.0000 - val_loss: 14.5501 - val_accuracy: 0.3154
Epoch 8966/10000
1/1 [==============================] - 0s 106ms/step - loss: 2.6476e-06 - accuracy: 1.0000 - val_loss: 14.5501 - val_accuracy: 0.3153
Epoch 8967/10000
1/1 [==============================] - 0s 107ms/step - loss: 2.6448e-06 - accuracy: 1.0000 - val_loss: 14.5507 - val_accuracy: 0.3154
Epoch 8968/10000
1/1 [==============================] - 0s 100ms/step - loss: 2.6443e-06 - accuracy: 1.0000 - val_loss: 14.5516 - val_accuracy: 0.3153
Epoch 8969/10000
1/1 [==============================] - 0s 103ms/step - loss: 2.6419e-06 - accuracy: 1.0000 - val_loss: 14.5526 - val_accuracy: 0.3154
Epoch 8970/10000
1/1 [==============================] - 0s 100ms/step - loss: 2.6419e-06 - accuracy: 1.0000 - val_loss: 14.5532 - val_accuracy: 0.3154
Epoch 8971/10000
1/1 [==============================] - 0s 107ms/step - loss: 2.6407e-06 - accuracy: 1.0000 - val_loss: 14.5528 - val_accuracy: 0.3154
Epoch 8972/10000
1/1 [==============================] - 0s 109ms/step - loss: 2.6395e-06 - accuracy: 1.0000 - val_loss: 14.5529 - val_accuracy: 0.3152
Epoch 8973/10000
1/1 [==============================] - 0s 102ms/step - loss: 2.6383e-06 - accuracy: 1.0000 - val_loss: 14.5534 - val_accuracy: 0.3153
Epoch 8974/10000
1/1 [==============================] - 0s 107ms/step - loss: 2.6371e-06 - accuracy: 1.0000 - val_loss: 14.5546 - val_accuracy: 0.3155
Epoch 8975/10000
1/1 [==============================] - 0s 105ms/step - loss: 2.6348e-06 - accuracy: 1.0000 - val_loss: 14.5556 - val_accuracy: 0.3154
Epoch 8976/10000
1/1 [==============================] - 0s 103ms/step - loss: 2.6319e-06 - accuracy: 1.0000 - val_loss: 14.5567 - val_accuracy: 0.3154
Epoch 8977/10000
1/1 [==============================] - 0s 109ms/step - loss: 2.6326e-06 - accuracy: 1.0000 - val_loss: 14.5569 - val_accuracy: 0.3153
Epoch 8978/10000
1/1 [==============================] - 0s 102ms/step - loss: 2.6297e-06 - accuracy: 1.0000 - val_loss: 14.5574 - val_accuracy: 0.3153
Epoch 8979/10000
1/1 [==============================] - 0s 104ms/step - loss: 2.6276e-06 - accuracy: 1.0000 - val_loss: 14.5578 - val_accuracy: 0.3153
Epoch 8980/10000
1/1 [==============================] - 0s 108ms/step - loss: 2.6243e-06 - accuracy: 1.0000 - val_loss: 14.5588 - val_accuracy: 0.3153
Epoch 8981/10000
1/1 [==============================] - 0s 101ms/step - loss: 2.6245e-06 - accuracy: 1.0000 - val_loss: 14.5591 - val_accuracy: 0.3154
Epoch 8982/10000
1/1 [==============================] - 0s 104ms/step - loss: 2.6228e-06 - accuracy: 1.0000 - val_loss: 14.5594 - val_accuracy: 0.3155
Epoch 8983/10000
1/1 [==============================] - 0s 103ms/step - loss: 2.6212e-06 - accuracy: 1.0000 - val_loss: 14.5595 - val_accuracy: 0.3152
Epoch 8984/10000
1/1 [==============================] - 0s 105ms/step - loss: 2.6195e-06 - accuracy: 1.0000 - val_loss: 14.5605 - val_accuracy: 0.3152
Epoch 8985/10000
1/1 [==============================] - 0s 109ms/step - loss: 2.6188e-06 - accuracy: 1.0000 - val_loss: 14.5621 - val_accuracy: 0.3154
Epoch 8986/10000
1/1 [==============================] - 0s 108ms/step - loss: 2.6169e-06 - accuracy: 1.0000 - val_loss: 14.5630 - val_accuracy: 0.3154
Epoch 8987/10000
1/1 [==============================] - 0s 102ms/step - loss: 2.6159e-06 - accuracy: 1.0000 - val_loss: 14.5630 - val_accuracy: 0.3153
Epoch 8988/10000
1/1 [==============================] - 0s 107ms/step - loss: 2.6150e-06 - accuracy: 1.0000 - val_loss: 14.5629 - val_accuracy: 0.3154
Epoch 8989/10000
1/1 [==============================] - 0s 102ms/step - loss: 2.6121e-06 - accuracy: 1.0000 - val_loss: 14.5633 - val_accuracy: 0.3153
Epoch 8990/10000
1/1 [==============================] - 0s 107ms/step - loss: 2.6133e-06 - accuracy: 1.0000 - val_loss: 14.5639 - val_accuracy: 0.3154
Epoch 8991/10000
1/1 [==============================] - 0s 105ms/step - loss: 2.6085e-06 - accuracy: 1.0000 - val_loss: 14.5650 - val_accuracy: 0.3154
Epoch 8992/10000
1/1 [==============================] - 0s 103ms/step - loss: 2.6083e-06 - accuracy: 1.0000 - val_loss: 14.5650 - val_accuracy: 0.3155
Epoch 8993/10000
1/1 [==============================] - 0s 105ms/step - loss: 2.6078e-06 - accuracy: 1.0000 - val_loss: 14.5658 - val_accuracy: 0.3154
Epoch 8994/10000
1/1 [==============================] - 0s 105ms/step - loss: 2.6057e-06 - accuracy: 1.0000 - val_loss: 14.5672 - val_accuracy: 0.3154
Epoch 8995/10000
1/1 [==============================] - 0s 105ms/step - loss: 2.6052e-06 - accuracy: 1.0000 - val_loss: 14.5677 - val_accuracy: 0.3153
Epoch 8996/10000
1/1 [==============================] - 0s 105ms/step - loss: 2.6004e-06 - accuracy: 1.0000 - val_loss: 14.5677 - val_accuracy: 0.3154
Epoch 8997/10000
1/1 [==============================] - 0s 102ms/step - loss: 2.5985e-06 - accuracy: 1.0000 - val_loss: 14.5675 - val_accuracy: 0.3154
Epoch 8998/10000
1/1 [==============================] - 0s 109ms/step - loss: 2.5999e-06 - accuracy: 1.0000 - val_loss: 14.5681 - val_accuracy: 0.3152
Epoch 8999/10000
1/1 [==============================] - 0s 108ms/step - loss: 2.5985e-06 - accuracy: 1.0000 - val_loss: 14.5695 - val_accuracy: 0.3154
Epoch 9000/10000
1/1 [==============================] - 0s 107ms/step - loss: 2.5964e-06 - accuracy: 1.0000 - val_loss: 14.5706 - val_accuracy: 0.3154
Epoch 9001/10000
1/1 [==============================] - 0s 103ms/step - loss: 2.5926e-06 - accuracy: 1.0000 - val_loss: 14.5715 - val_accuracy: 0.3154
Epoch 9002/10000
1/1 [==============================] - 0s 108ms/step - loss: 2.5914e-06 - accuracy: 1.0000 - val_loss: 14.5718 - val_accuracy: 0.3154
Epoch 9003/10000
1/1 [==============================] - 0s 107ms/step - loss: 2.5890e-06 - accuracy: 1.0000 - val_loss: 14.5719 - val_accuracy: 0.3154
Epoch 9004/10000
1/1 [==============================] - 0s 111ms/step - loss: 2.5885e-06 - accuracy: 1.0000 - val_loss: 14.5724 - val_accuracy: 0.3154
Epoch 9005/10000
1/1 [==============================] - 0s 108ms/step - loss: 2.5854e-06 - accuracy: 1.0000 - val_loss: 14.5733 - val_accuracy: 0.3154
Epoch 9006/10000
1/1 [==============================] - 0s 113ms/step - loss: 2.5861e-06 - accuracy: 1.0000 - val_loss: 14.5739 - val_accuracy: 0.3154
Epoch 9007/10000
1/1 [==============================] - 0s 104ms/step - loss: 2.5825e-06 - accuracy: 1.0000 - val_loss: 14.5740 - val_accuracy: 0.3154
Epoch 9008/10000
1/1 [==============================] - 0s 114ms/step - loss: 2.5806e-06 - accuracy: 1.0000 - val_loss: 14.5743 - val_accuracy: 0.3154
Epoch 9009/10000
1/1 [==============================] - 0s 107ms/step - loss: 2.5799e-06 - accuracy: 1.0000 - val_loss: 14.5752 - val_accuracy: 0.3154
Epoch 9010/10000
1/1 [==============================] - 0s 103ms/step - loss: 2.5790e-06 - accuracy: 1.0000 - val_loss: 14.5767 - val_accuracy: 0.3154
Epoch 9011/10000
1/1 [==============================] - 0s 102ms/step - loss: 2.5771e-06 - accuracy: 1.0000 - val_loss: 14.5772 - val_accuracy: 0.3154
Epoch 9012/10000
1/1 [==============================] - 0s 106ms/step - loss: 2.5768e-06 - accuracy: 1.0000 - val_loss: 14.5769 - val_accuracy: 0.3154
Epoch 9013/10000
1/1 [==============================] - 0s 108ms/step - loss: 2.5744e-06 - accuracy: 1.0000 - val_loss: 14.5770 - val_accuracy: 0.3154
Epoch 9014/10000
1/1 [==============================] - 0s 111ms/step - loss: 2.5737e-06 - accuracy: 1.0000 - val_loss: 14.5782 - val_accuracy: 0.3154
Epoch 9015/10000
1/1 [==============================] - 0s 109ms/step - loss: 2.5720e-06 - accuracy: 1.0000 - val_loss: 14.5787 - val_accuracy: 0.3155
Epoch 9016/10000
1/1 [==============================] - 0s 112ms/step - loss: 2.5685e-06 - accuracy: 1.0000 - val_loss: 14.5786 - val_accuracy: 0.3155
Epoch 9017/10000
1/1 [==============================] - 0s 107ms/step - loss: 2.5673e-06 - accuracy: 1.0000 - val_loss: 14.5784 - val_accuracy: 0.3154
Epoch 9018/10000
1/1 [==============================] - 0s 107ms/step - loss: 2.5673e-06 - accuracy: 1.0000 - val_loss: 14.5792 - val_accuracy: 0.3154
Epoch 9019/10000
1/1 [==============================] - 0s 109ms/step - loss: 2.5651e-06 - accuracy: 1.0000 - val_loss: 14.5808 - val_accuracy: 0.3156
Epoch 9020/10000
1/1 [==============================] - 0s 105ms/step - loss: 2.5637e-06 - accuracy: 1.0000 - val_loss: 14.5820 - val_accuracy: 0.3154
Epoch 9021/10000
1/1 [==============================] - 0s 105ms/step - loss: 2.5608e-06 - accuracy: 1.0000 - val_loss: 14.5831 - val_accuracy: 0.3154
Epoch 9022/10000
1/1 [==============================] - 0s 109ms/step - loss: 2.5611e-06 - accuracy: 1.0000 - val_loss: 14.5833 - val_accuracy: 0.3155
Epoch 9023/10000
1/1 [==============================] - 0s 116ms/step - loss: 2.5597e-06 - accuracy: 1.0000 - val_loss: 14.5834 - val_accuracy: 0.3155
Epoch 9024/10000
1/1 [==============================] - 0s 115ms/step - loss: 2.5563e-06 - accuracy: 1.0000 - val_loss: 14.5836 - val_accuracy: 0.3155
Epoch 9025/10000
1/1 [==============================] - 0s 108ms/step - loss: 2.5568e-06 - accuracy: 1.0000 - val_loss: 14.5840 - val_accuracy: 0.3154
Epoch 9026/10000
1/1 [==============================] - 0s 117ms/step - loss: 2.5568e-06 - accuracy: 1.0000 - val_loss: 14.5854 - val_accuracy: 0.3154
Epoch 9027/10000
1/1 [==============================] - 0s 107ms/step - loss: 2.5530e-06 - accuracy: 1.0000 - val_loss: 14.5868 - val_accuracy: 0.3155
Epoch 9028/10000
1/1 [==============================] - 0s 109ms/step - loss: 2.5492e-06 - accuracy: 1.0000 - val_loss: 14.5867 - val_accuracy: 0.3155
Epoch 9029/10000
1/1 [==============================] - 0s 103ms/step - loss: 2.5473e-06 - accuracy: 1.0000 - val_loss: 14.5863 - val_accuracy: 0.3155
Epoch 9030/10000
1/1 [==============================] - 0s 105ms/step - loss: 2.5461e-06 - accuracy: 1.0000 - val_loss: 14.5865 - val_accuracy: 0.3155
Epoch 9031/10000
1/1 [==============================] - 0s 107ms/step - loss: 2.5444e-06 - accuracy: 1.0000 - val_loss: 14.5878 - val_accuracy: 0.3154
Epoch 9032/10000
1/1 [==============================] - 0s 111ms/step - loss: 2.5430e-06 - accuracy: 1.0000 - val_loss: 14.5895 - val_accuracy: 0.3155
Epoch 9033/10000
1/1 [==============================] - 0s 117ms/step - loss: 2.5432e-06 - accuracy: 1.0000 - val_loss: 14.5903 - val_accuracy: 0.3155
Epoch 9034/10000
1/1 [==============================] - 0s 108ms/step - loss: 2.5403e-06 - accuracy: 1.0000 - val_loss: 14.5896 - val_accuracy: 0.3155
Epoch 9035/10000
1/1 [==============================] - 0s 108ms/step - loss: 2.5384e-06 - accuracy: 1.0000 - val_loss: 14.5894 - val_accuracy: 0.3156
Epoch 9036/10000
1/1 [==============================] - 0s 117ms/step - loss: 2.5346e-06 - accuracy: 1.0000 - val_loss: 14.5903 - val_accuracy: 0.3156
Epoch 9037/10000
1/1 [==============================] - 0s 112ms/step - loss: 2.5334e-06 - accuracy: 1.0000 - val_loss: 14.5917 - val_accuracy: 0.3156
Epoch 9038/10000
1/1 [==============================] - 0s 110ms/step - loss: 2.5344e-06 - accuracy: 1.0000 - val_loss: 14.5926 - val_accuracy: 0.3155
Epoch 9039/10000
1/1 [==============================] - 0s 112ms/step - loss: 2.5329e-06 - accuracy: 1.0000 - val_loss: 14.5931 - val_accuracy: 0.3155
Epoch 9040/10000
1/1 [==============================] - 0s 108ms/step - loss: 2.5320e-06 - accuracy: 1.0000 - val_loss: 14.5930 - val_accuracy: 0.3156
Epoch 9041/10000
1/1 [==============================] - 0s 107ms/step - loss: 2.5291e-06 - accuracy: 1.0000 - val_loss: 14.5932 - val_accuracy: 0.3156
Epoch 9042/10000
1/1 [==============================] - 0s 108ms/step - loss: 2.5277e-06 - accuracy: 1.0000 - val_loss: 14.5936 - val_accuracy: 0.3156
Epoch 9043/10000
1/1 [==============================] - 0s 110ms/step - loss: 2.5275e-06 - accuracy: 1.0000 - val_loss: 14.5944 - val_accuracy: 0.3156
Epoch 9044/10000
1/1 [==============================] - 0s 105ms/step - loss: 2.5241e-06 - accuracy: 1.0000 - val_loss: 14.5952 - val_accuracy: 0.3156
Epoch 9045/10000
1/1 [==============================] - 0s 103ms/step - loss: 2.5248e-06 - accuracy: 1.0000 - val_loss: 14.5963 - val_accuracy: 0.3155
Epoch 9046/10000
1/1 [==============================] - 0s 106ms/step - loss: 2.5232e-06 - accuracy: 1.0000 - val_loss: 14.5972 - val_accuracy: 0.3155
Epoch 9047/10000
1/1 [==============================] - 0s 104ms/step - loss: 2.5196e-06 - accuracy: 1.0000 - val_loss: 14.5974 - val_accuracy: 0.3155
Epoch 9048/10000
1/1 [==============================] - 0s 104ms/step - loss: 2.5186e-06 - accuracy: 1.0000 - val_loss: 14.5975 - val_accuracy: 0.3156
Epoch 9049/10000
1/1 [==============================] - 0s 106ms/step - loss: 2.5189e-06 - accuracy: 1.0000 - val_loss: 14.5980 - val_accuracy: 0.3156
Epoch 9050/10000
1/1 [==============================] - 0s 105ms/step - loss: 2.5177e-06 - accuracy: 1.0000 - val_loss: 14.5990 - val_accuracy: 0.3155
Epoch 9051/10000
1/1 [==============================] - 0s 108ms/step - loss: 2.5146e-06 - accuracy: 1.0000 - val_loss: 14.6000 - val_accuracy: 0.3155
Epoch 9052/10000
1/1 [==============================] - 0s 101ms/step - loss: 2.5117e-06 - accuracy: 1.0000 - val_loss: 14.6003 - val_accuracy: 0.3155
Epoch 9053/10000
1/1 [==============================] - 0s 105ms/step - loss: 2.5120e-06 - accuracy: 1.0000 - val_loss: 14.6006 - val_accuracy: 0.3155
Epoch 9054/10000
1/1 [==============================] - 0s 109ms/step - loss: 2.5098e-06 - accuracy: 1.0000 - val_loss: 14.6011 - val_accuracy: 0.3155
Epoch 9055/10000
1/1 [==============================] - 0s 103ms/step - loss: 2.5086e-06 - accuracy: 1.0000 - val_loss: 14.6018 - val_accuracy: 0.3155
Epoch 9056/10000
1/1 [==============================] - 0s 108ms/step - loss: 2.5093e-06 - accuracy: 1.0000 - val_loss: 14.6027 - val_accuracy: 0.3156
Epoch 9057/10000
1/1 [==============================] - 0s 109ms/step - loss: 2.5065e-06 - accuracy: 1.0000 - val_loss: 14.6034 - val_accuracy: 0.3156
Epoch 9058/10000
1/1 [==============================] - 0s 106ms/step - loss: 2.5048e-06 - accuracy: 1.0000 - val_loss: 14.6036 - val_accuracy: 0.3156
Epoch 9059/10000
1/1 [==============================] - 0s 113ms/step - loss: 2.5031e-06 - accuracy: 1.0000 - val_loss: 14.6039 - val_accuracy: 0.3156
Epoch 9060/10000
1/1 [==============================] - 0s 103ms/step - loss: 2.5008e-06 - accuracy: 1.0000 - val_loss: 14.6040 - val_accuracy: 0.3156
Epoch 9061/10000
1/1 [==============================] - 0s 105ms/step - loss: 2.5003e-06 - accuracy: 1.0000 - val_loss: 14.6049 - val_accuracy: 0.3156
Epoch 9062/10000
1/1 [==============================] - 0s 107ms/step - loss: 2.4986e-06 - accuracy: 1.0000 - val_loss: 14.6060 - val_accuracy: 0.3155
Epoch 9063/10000
1/1 [==============================] - 0s 107ms/step - loss: 2.4974e-06 - accuracy: 1.0000 - val_loss: 14.6067 - val_accuracy: 0.3155
Epoch 9064/10000
1/1 [==============================] - 0s 106ms/step - loss: 2.4977e-06 - accuracy: 1.0000 - val_loss: 14.6070 - val_accuracy: 0.3156
Epoch 9065/10000
1/1 [==============================] - 0s 109ms/step - loss: 2.4958e-06 - accuracy: 1.0000 - val_loss: 14.6076 - val_accuracy: 0.3155
Epoch 9066/10000
1/1 [==============================] - 0s 102ms/step - loss: 2.4941e-06 - accuracy: 1.0000 - val_loss: 14.6081 - val_accuracy: 0.3155
Epoch 9067/10000
1/1 [==============================] - 0s 105ms/step - loss: 2.4915e-06 - accuracy: 1.0000 - val_loss: 14.6091 - val_accuracy: 0.3156
Epoch 9068/10000
1/1 [==============================] - 0s 108ms/step - loss: 2.4919e-06 - accuracy: 1.0000 - val_loss: 14.6093 - val_accuracy: 0.3157
Epoch 9069/10000
1/1 [==============================] - 0s 106ms/step - loss: 2.4893e-06 - accuracy: 1.0000 - val_loss: 14.6093 - val_accuracy: 0.3156
Epoch 9070/10000
1/1 [==============================] - 0s 106ms/step - loss: 2.4905e-06 - accuracy: 1.0000 - val_loss: 14.6097 - val_accuracy: 0.3156
Epoch 9071/10000
1/1 [==============================] - 0s 106ms/step - loss: 2.4884e-06 - accuracy: 1.0000 - val_loss: 14.6103 - val_accuracy: 0.3156
Epoch 9072/10000
1/1 [==============================] - 0s 105ms/step - loss: 2.4862e-06 - accuracy: 1.0000 - val_loss: 14.6115 - val_accuracy: 0.3156
Epoch 9073/10000
1/1 [==============================] - 0s 107ms/step - loss: 2.4848e-06 - accuracy: 1.0000 - val_loss: 14.6125 - val_accuracy: 0.3156
Epoch 9074/10000
1/1 [==============================] - 0s 103ms/step - loss: 2.4841e-06 - accuracy: 1.0000 - val_loss: 14.6132 - val_accuracy: 0.3156
Epoch 9075/10000
1/1 [==============================] - 0s 104ms/step - loss: 2.4822e-06 - accuracy: 1.0000 - val_loss: 14.6138 - val_accuracy: 0.3155
Epoch 9076/10000
1/1 [==============================] - 0s 107ms/step - loss: 2.4795e-06 - accuracy: 1.0000 - val_loss: 14.6143 - val_accuracy: 0.3155
Epoch 9077/10000
1/1 [==============================] - 0s 105ms/step - loss: 2.4779e-06 - accuracy: 1.0000 - val_loss: 14.6148 - val_accuracy: 0.3155
Epoch 9078/10000
1/1 [==============================] - 0s 103ms/step - loss: 2.4767e-06 - accuracy: 1.0000 - val_loss: 14.6152 - val_accuracy: 0.3155
Epoch 9079/10000
1/1 [==============================] - 0s 104ms/step - loss: 2.4760e-06 - accuracy: 1.0000 - val_loss: 14.6155 - val_accuracy: 0.3155
Epoch 9080/10000
1/1 [==============================] - 0s 108ms/step - loss: 2.4733e-06 - accuracy: 1.0000 - val_loss: 14.6166 - val_accuracy: 0.3157
Epoch 9081/10000
1/1 [==============================] - 0s 112ms/step - loss: 2.4717e-06 - accuracy: 1.0000 - val_loss: 14.6173 - val_accuracy: 0.3155
Epoch 9082/10000
1/1 [==============================] - 0s 104ms/step - loss: 2.4691e-06 - accuracy: 1.0000 - val_loss: 14.6172 - val_accuracy: 0.3155
Epoch 9083/10000
1/1 [==============================] - 0s 108ms/step - loss: 2.4700e-06 - accuracy: 1.0000 - val_loss: 14.6178 - val_accuracy: 0.3155
Epoch 9084/10000
1/1 [==============================] - 0s 105ms/step - loss: 2.4698e-06 - accuracy: 1.0000 - val_loss: 14.6188 - val_accuracy: 0.3156
Epoch 9085/10000
1/1 [==============================] - 0s 109ms/step - loss: 2.4650e-06 - accuracy: 1.0000 - val_loss: 14.6198 - val_accuracy: 0.3155
Epoch 9086/10000
1/1 [==============================] - 0s 105ms/step - loss: 2.4660e-06 - accuracy: 1.0000 - val_loss: 14.6201 - val_accuracy: 0.3155
Epoch 9087/10000
1/1 [==============================] - 0s 103ms/step - loss: 2.4631e-06 - accuracy: 1.0000 - val_loss: 14.6204 - val_accuracy: 0.3155
Epoch 9088/10000
1/1 [==============================] - 0s 106ms/step - loss: 2.4619e-06 - accuracy: 1.0000 - val_loss: 14.6206 - val_accuracy: 0.3157
Epoch 9089/10000
1/1 [==============================] - 0s 111ms/step - loss: 2.4590e-06 - accuracy: 1.0000 - val_loss: 14.6207 - val_accuracy: 0.3156
Epoch 9090/10000
1/1 [==============================] - 0s 107ms/step - loss: 2.4593e-06 - accuracy: 1.0000 - val_loss: 14.6210 - val_accuracy: 0.3156
Epoch 9091/10000
1/1 [==============================] - 0s 109ms/step - loss: 2.4586e-06 - accuracy: 1.0000 - val_loss: 14.6219 - val_accuracy: 0.3157
Epoch 9092/10000
1/1 [==============================] - 0s 106ms/step - loss: 2.4567e-06 - accuracy: 1.0000 - val_loss: 14.6232 - val_accuracy: 0.3156
Epoch 9093/10000
1/1 [==============================] - 0s 105ms/step - loss: 2.4538e-06 - accuracy: 1.0000 - val_loss: 14.6244 - val_accuracy: 0.3156
Epoch 9094/10000
1/1 [==============================] - 0s 107ms/step - loss: 2.4531e-06 - accuracy: 1.0000 - val_loss: 14.6245 - val_accuracy: 0.3156
Epoch 9095/10000
1/1 [==============================] - 0s 109ms/step - loss: 2.4521e-06 - accuracy: 1.0000 - val_loss: 14.6250 - val_accuracy: 0.3156
Epoch 9096/10000
1/1 [==============================] - 0s 104ms/step - loss: 2.4507e-06 - accuracy: 1.0000 - val_loss: 14.6255 - val_accuracy: 0.3156
Epoch 9097/10000
1/1 [==============================] - 0s 101ms/step - loss: 2.4490e-06 - accuracy: 1.0000 - val_loss: 14.6260 - val_accuracy: 0.3155
Epoch 9098/10000
1/1 [==============================] - 0s 107ms/step - loss: 2.4481e-06 - accuracy: 1.0000 - val_loss: 14.6268 - val_accuracy: 0.3155
Epoch 9099/10000
1/1 [==============================] - 0s 107ms/step - loss: 2.4455e-06 - accuracy: 1.0000 - val_loss: 14.6275 - val_accuracy: 0.3156
Epoch 9100/10000
1/1 [==============================] - 0s 105ms/step - loss: 2.4459e-06 - accuracy: 1.0000 - val_loss: 14.6280 - val_accuracy: 0.3157
Epoch 9101/10000
1/1 [==============================] - 0s 105ms/step - loss: 2.4428e-06 - accuracy: 1.0000 - val_loss: 14.6287 - val_accuracy: 0.3157
Epoch 9102/10000
1/1 [==============================] - 0s 107ms/step - loss: 2.4407e-06 - accuracy: 1.0000 - val_loss: 14.6289 - val_accuracy: 0.3157
Epoch 9103/10000
1/1 [==============================] - 0s 110ms/step - loss: 2.4409e-06 - accuracy: 1.0000 - val_loss: 14.6295 - val_accuracy: 0.3156
Epoch 9104/10000
1/1 [==============================] - 0s 112ms/step - loss: 2.4393e-06 - accuracy: 1.0000 - val_loss: 14.6307 - val_accuracy: 0.3156
Epoch 9105/10000
1/1 [==============================] - 0s 109ms/step - loss: 2.4373e-06 - accuracy: 1.0000 - val_loss: 14.6314 - val_accuracy: 0.3155
Epoch 9106/10000
1/1 [==============================] - 0s 111ms/step - loss: 2.4371e-06 - accuracy: 1.0000 - val_loss: 14.6312 - val_accuracy: 0.3158
Epoch 9107/10000
1/1 [==============================] - 0s 106ms/step - loss: 2.4338e-06 - accuracy: 1.0000 - val_loss: 14.6312 - val_accuracy: 0.3158
Epoch 9108/10000
1/1 [==============================] - 0s 113ms/step - loss: 2.4304e-06 - accuracy: 1.0000 - val_loss: 14.6319 - val_accuracy: 0.3158
Epoch 9109/10000
1/1 [==============================] - 0s 103ms/step - loss: 2.4319e-06 - accuracy: 1.0000 - val_loss: 14.6333 - val_accuracy: 0.3156
Epoch 9110/10000
1/1 [==============================] - 0s 114ms/step - loss: 2.4300e-06 - accuracy: 1.0000 - val_loss: 14.6344 - val_accuracy: 0.3156
Epoch 9111/10000
1/1 [==============================] - 0s 110ms/step - loss: 2.4288e-06 - accuracy: 1.0000 - val_loss: 14.6343 - val_accuracy: 0.3156
Epoch 9112/10000
1/1 [==============================] - 0s 104ms/step - loss: 2.4271e-06 - accuracy: 1.0000 - val_loss: 14.6343 - val_accuracy: 0.3157
Epoch 9113/10000
1/1 [==============================] - 0s 112ms/step - loss: 2.4252e-06 - accuracy: 1.0000 - val_loss: 14.6346 - val_accuracy: 0.3156
Epoch 9114/10000
1/1 [==============================] - 0s 106ms/step - loss: 2.4245e-06 - accuracy: 1.0000 - val_loss: 14.6351 - val_accuracy: 0.3157
Epoch 9115/10000
1/1 [==============================] - 0s 107ms/step - loss: 2.4223e-06 - accuracy: 1.0000 - val_loss: 14.6358 - val_accuracy: 0.3158
Epoch 9116/10000
1/1 [==============================] - 0s 107ms/step - loss: 2.4214e-06 - accuracy: 1.0000 - val_loss: 14.6366 - val_accuracy: 0.3157
Epoch 9117/10000
1/1 [==============================] - 0s 110ms/step - loss: 2.4197e-06 - accuracy: 1.0000 - val_loss: 14.6375 - val_accuracy: 0.3156
Epoch 9118/10000
1/1 [==============================] - 0s 108ms/step - loss: 2.4178e-06 - accuracy: 1.0000 - val_loss: 14.6387 - val_accuracy: 0.3157
Epoch 9119/10000
1/1 [==============================] - 0s 112ms/step - loss: 2.4176e-06 - accuracy: 1.0000 - val_loss: 14.6392 - val_accuracy: 0.3155
Epoch 9120/10000
1/1 [==============================] - 0s 102ms/step - loss: 2.4149e-06 - accuracy: 1.0000 - val_loss: 14.6392 - val_accuracy: 0.3157
Epoch 9121/10000
1/1 [==============================] - 0s 104ms/step - loss: 2.4147e-06 - accuracy: 1.0000 - val_loss: 14.6397 - val_accuracy: 0.3156
Epoch 9122/10000
1/1 [==============================] - 0s 110ms/step - loss: 2.4128e-06 - accuracy: 1.0000 - val_loss: 14.6408 - val_accuracy: 0.3156
Epoch 9123/10000
1/1 [==============================] - 0s 102ms/step - loss: 2.4109e-06 - accuracy: 1.0000 - val_loss: 14.6416 - val_accuracy: 0.3156
Epoch 9124/10000
1/1 [==============================] - 0s 104ms/step - loss: 2.4099e-06 - accuracy: 1.0000 - val_loss: 14.6420 - val_accuracy: 0.3155
Epoch 9125/10000
1/1 [==============================] - 0s 102ms/step - loss: 2.4071e-06 - accuracy: 1.0000 - val_loss: 14.6420 - val_accuracy: 0.3155
Epoch 9126/10000
1/1 [==============================] - 0s 109ms/step - loss: 2.4063e-06 - accuracy: 1.0000 - val_loss: 14.6425 - val_accuracy: 0.3154
Epoch 9127/10000
1/1 [==============================] - 0s 102ms/step - loss: 2.4052e-06 - accuracy: 1.0000 - val_loss: 14.6431 - val_accuracy: 0.3155
Epoch 9128/10000
1/1 [==============================] - 0s 101ms/step - loss: 2.4028e-06 - accuracy: 1.0000 - val_loss: 14.6438 - val_accuracy: 0.3157
Epoch 9129/10000
1/1 [==============================] - 0s 111ms/step - loss: 2.4028e-06 - accuracy: 1.0000 - val_loss: 14.6442 - val_accuracy: 0.3157
Epoch 9130/10000
1/1 [==============================] - 0s 103ms/step - loss: 2.3999e-06 - accuracy: 1.0000 - val_loss: 14.6450 - val_accuracy: 0.3156
Epoch 9131/10000
1/1 [==============================] - 0s 104ms/step - loss: 2.3985e-06 - accuracy: 1.0000 - val_loss: 14.6454 - val_accuracy: 0.3156
Epoch 9132/10000
1/1 [==============================] - 0s 107ms/step - loss: 2.3973e-06 - accuracy: 1.0000 - val_loss: 14.6464 - val_accuracy: 0.3156
Epoch 9133/10000
1/1 [==============================] - 0s 107ms/step - loss: 2.3951e-06 - accuracy: 1.0000 - val_loss: 14.6472 - val_accuracy: 0.3155
Epoch 9134/10000
1/1 [==============================] - 0s 108ms/step - loss: 2.3940e-06 - accuracy: 1.0000 - val_loss: 14.6476 - val_accuracy: 0.3155
Epoch 9135/10000
1/1 [==============================] - 0s 107ms/step - loss: 2.3928e-06 - accuracy: 1.0000 - val_loss: 14.6483 - val_accuracy: 0.3156
Epoch 9136/10000
1/1 [==============================] - 0s 104ms/step - loss: 2.3901e-06 - accuracy: 1.0000 - val_loss: 14.6489 - val_accuracy: 0.3156
Epoch 9137/10000
1/1 [==============================] - 0s 106ms/step - loss: 2.3894e-06 - accuracy: 1.0000 - val_loss: 14.6490 - val_accuracy: 0.3157
Epoch 9138/10000
1/1 [==============================] - 0s 121ms/step - loss: 2.3887e-06 - accuracy: 1.0000 - val_loss: 14.6493 - val_accuracy: 0.3156
Epoch 9139/10000
1/1 [==============================] - 0s 137ms/step - loss: 2.3878e-06 - accuracy: 1.0000 - val_loss: 14.6504 - val_accuracy: 0.3155
Epoch 9140/10000
1/1 [==============================] - 0s 117ms/step - loss: 2.3863e-06 - accuracy: 1.0000 - val_loss: 14.6516 - val_accuracy: 0.3156
Epoch 9141/10000
1/1 [==============================] - 0s 121ms/step - loss: 2.3854e-06 - accuracy: 1.0000 - val_loss: 14.6518 - val_accuracy: 0.3156
Epoch 9142/10000
1/1 [==============================] - 0s 131ms/step - loss: 2.3839e-06 - accuracy: 1.0000 - val_loss: 14.6521 - val_accuracy: 0.3157
Epoch 9143/10000
1/1 [==============================] - 0s 137ms/step - loss: 2.3827e-06 - accuracy: 1.0000 - val_loss: 14.6527 - val_accuracy: 0.3158
Epoch 9144/10000
1/1 [==============================] - 0s 139ms/step - loss: 2.3813e-06 - accuracy: 1.0000 - val_loss: 14.6531 - val_accuracy: 0.3155
Epoch 9145/10000
1/1 [==============================] - 0s 112ms/step - loss: 2.3780e-06 - accuracy: 1.0000 - val_loss: 14.6540 - val_accuracy: 0.3154
Epoch 9146/10000
1/1 [==============================] - 0s 117ms/step - loss: 2.3765e-06 - accuracy: 1.0000 - val_loss: 14.6548 - val_accuracy: 0.3155
Epoch 9147/10000
1/1 [==============================] - 0s 118ms/step - loss: 2.3761e-06 - accuracy: 1.0000 - val_loss: 14.6555 - val_accuracy: 0.3157
Epoch 9148/10000
1/1 [==============================] - 0s 116ms/step - loss: 2.3744e-06 - accuracy: 1.0000 - val_loss: 14.6559 - val_accuracy: 0.3156
Epoch 9149/10000
1/1 [==============================] - 0s 105ms/step - loss: 2.3723e-06 - accuracy: 1.0000 - val_loss: 14.6555 - val_accuracy: 0.3157
Epoch 9150/10000
1/1 [==============================] - 0s 115ms/step - loss: 2.3725e-06 - accuracy: 1.0000 - val_loss: 14.6560 - val_accuracy: 0.3156
Epoch 9151/10000
1/1 [==============================] - 0s 105ms/step - loss: 2.3711e-06 - accuracy: 1.0000 - val_loss: 14.6569 - val_accuracy: 0.3156
Epoch 9152/10000
1/1 [==============================] - 0s 106ms/step - loss: 2.3682e-06 - accuracy: 1.0000 - val_loss: 14.6579 - val_accuracy: 0.3157
Epoch 9153/10000
1/1 [==============================] - 0s 105ms/step - loss: 2.3696e-06 - accuracy: 1.0000 - val_loss: 14.6589 - val_accuracy: 0.3155
Epoch 9154/10000
1/1 [==============================] - 0s 107ms/step - loss: 2.3672e-06 - accuracy: 1.0000 - val_loss: 14.6594 - val_accuracy: 0.3157
Epoch 9155/10000
1/1 [==============================] - 0s 105ms/step - loss: 2.3646e-06 - accuracy: 1.0000 - val_loss: 14.6594 - val_accuracy: 0.3157
Epoch 9156/10000
1/1 [==============================] - 0s 104ms/step - loss: 2.3644e-06 - accuracy: 1.0000 - val_loss: 14.6600 - val_accuracy: 0.3156
Epoch 9157/10000
1/1 [==============================] - 0s 109ms/step - loss: 2.3630e-06 - accuracy: 1.0000 - val_loss: 14.6613 - val_accuracy: 0.3154
Epoch 9158/10000
1/1 [==============================] - 0s 108ms/step - loss: 2.3615e-06 - accuracy: 1.0000 - val_loss: 14.6620 - val_accuracy: 0.3156
Epoch 9159/10000
1/1 [==============================] - 0s 103ms/step - loss: 2.3601e-06 - accuracy: 1.0000 - val_loss: 14.6620 - val_accuracy: 0.3157
Epoch 9160/10000
1/1 [==============================] - 0s 100ms/step - loss: 2.3599e-06 - accuracy: 1.0000 - val_loss: 14.6620 - val_accuracy: 0.3155
Epoch 9161/10000
1/1 [==============================] - 0s 109ms/step - loss: 2.3587e-06 - accuracy: 1.0000 - val_loss: 14.6628 - val_accuracy: 0.3156
Epoch 9162/10000
1/1 [==============================] - 0s 103ms/step - loss: 2.3565e-06 - accuracy: 1.0000 - val_loss: 14.6641 - val_accuracy: 0.3156
Epoch 9163/10000
1/1 [==============================] - 0s 110ms/step - loss: 2.3527e-06 - accuracy: 1.0000 - val_loss: 14.6647 - val_accuracy: 0.3157
Epoch 9164/10000
1/1 [==============================] - 0s 107ms/step - loss: 2.3510e-06 - accuracy: 1.0000 - val_loss: 14.6648 - val_accuracy: 0.3155
Epoch 9165/10000
1/1 [==============================] - 0s 106ms/step - loss: 2.3518e-06 - accuracy: 1.0000 - val_loss: 14.6650 - val_accuracy: 0.3156
Epoch 9166/10000
1/1 [==============================] - 0s 102ms/step - loss: 2.3515e-06 - accuracy: 1.0000 - val_loss: 14.6660 - val_accuracy: 0.3155
Epoch 9167/10000
1/1 [==============================] - 0s 109ms/step - loss: 2.3491e-06 - accuracy: 1.0000 - val_loss: 14.6674 - val_accuracy: 0.3156
Epoch 9168/10000
1/1 [==============================] - 0s 102ms/step - loss: 2.3477e-06 - accuracy: 1.0000 - val_loss: 14.6674 - val_accuracy: 0.3156
Epoch 9169/10000
1/1 [==============================] - 0s 102ms/step - loss: 2.3477e-06 - accuracy: 1.0000 - val_loss: 14.6663 - val_accuracy: 0.3154
Epoch 9170/10000
1/1 [==============================] - 0s 102ms/step - loss: 2.3463e-06 - accuracy: 1.0000 - val_loss: 14.6659 - val_accuracy: 0.3154
Epoch 9171/10000
1/1 [==============================] - 0s 100ms/step - loss: 2.3460e-06 - accuracy: 1.0000 - val_loss: 14.6670 - val_accuracy: 0.3153
Epoch 9172/10000
1/1 [==============================] - 0s 102ms/step - loss: 2.3444e-06 - accuracy: 1.0000 - val_loss: 14.6687 - val_accuracy: 0.3153
Epoch 9173/10000
1/1 [==============================] - 0s 102ms/step - loss: 2.3436e-06 - accuracy: 1.0000 - val_loss: 14.6697 - val_accuracy: 0.3156
Epoch 9174/10000
1/1 [==============================] - 0s 103ms/step - loss: 2.3394e-06 - accuracy: 1.0000 - val_loss: 14.6706 - val_accuracy: 0.3156
Epoch 9175/10000
1/1 [==============================] - 0s 102ms/step - loss: 2.3374e-06 - accuracy: 1.0000 - val_loss: 14.6720 - val_accuracy: 0.3156
Epoch 9176/10000
1/1 [==============================] - 0s 108ms/step - loss: 2.3382e-06 - accuracy: 1.0000 - val_loss: 14.6726 - val_accuracy: 0.3157
Epoch 9177/10000
1/1 [==============================] - 0s 104ms/step - loss: 2.3358e-06 - accuracy: 1.0000 - val_loss: 14.6724 - val_accuracy: 0.3155
Epoch 9178/10000
1/1 [==============================] - 0s 103ms/step - loss: 2.3353e-06 - accuracy: 1.0000 - val_loss: 14.6722 - val_accuracy: 0.3154
Epoch 9179/10000
1/1 [==============================] - 0s 102ms/step - loss: 2.3329e-06 - accuracy: 1.0000 - val_loss: 14.6726 - val_accuracy: 0.3155
Epoch 9180/10000
1/1 [==============================] - 0s 106ms/step - loss: 2.3305e-06 - accuracy: 1.0000 - val_loss: 14.6740 - val_accuracy: 0.3155
Epoch 9181/10000
1/1 [==============================] - 0s 99ms/step - loss: 2.3281e-06 - accuracy: 1.0000 - val_loss: 14.6753 - val_accuracy: 0.3155
Epoch 9182/10000
1/1 [==============================] - 0s 104ms/step - loss: 2.3286e-06 - accuracy: 1.0000 - val_loss: 14.6756 - val_accuracy: 0.3157
Epoch 9183/10000
1/1 [==============================] - 0s 108ms/step - loss: 2.3274e-06 - accuracy: 1.0000 - val_loss: 14.6758 - val_accuracy: 0.3155
Epoch 9184/10000
1/1 [==============================] - 0s 106ms/step - loss: 2.3255e-06 - accuracy: 1.0000 - val_loss: 14.6762 - val_accuracy: 0.3155
Epoch 9185/10000
1/1 [==============================] - 0s 101ms/step - loss: 2.3246e-06 - accuracy: 1.0000 - val_loss: 14.6769 - val_accuracy: 0.3157
Epoch 9186/10000
1/1 [==============================] - 0s 103ms/step - loss: 2.3217e-06 - accuracy: 1.0000 - val_loss: 14.6780 - val_accuracy: 0.3157
Epoch 9187/10000
1/1 [==============================] - 0s 101ms/step - loss: 2.3212e-06 - accuracy: 1.0000 - val_loss: 14.6783 - val_accuracy: 0.3157
Epoch 9188/10000
1/1 [==============================] - 0s 100ms/step - loss: 2.3198e-06 - accuracy: 1.0000 - val_loss: 14.6784 - val_accuracy: 0.3155
Epoch 9189/10000
1/1 [==============================] - 0s 102ms/step - loss: 2.3208e-06 - accuracy: 1.0000 - val_loss: 14.6788 - val_accuracy: 0.3155
Epoch 9190/10000
1/1 [==============================] - 0s 106ms/step - loss: 2.3179e-06 - accuracy: 1.0000 - val_loss: 14.6797 - val_accuracy: 0.3154
Epoch 9191/10000
1/1 [==============================] - 0s 110ms/step - loss: 2.3158e-06 - accuracy: 1.0000 - val_loss: 14.6807 - val_accuracy: 0.3156
Epoch 9192/10000
1/1 [==============================] - 0s 105ms/step - loss: 2.3158e-06 - accuracy: 1.0000 - val_loss: 14.6815 - val_accuracy: 0.3157
Epoch 9193/10000
1/1 [==============================] - 0s 107ms/step - loss: 2.3138e-06 - accuracy: 1.0000 - val_loss: 14.6818 - val_accuracy: 0.3154
Epoch 9194/10000
1/1 [==============================] - 0s 103ms/step - loss: 2.3117e-06 - accuracy: 1.0000 - val_loss: 14.6814 - val_accuracy: 0.3154
Epoch 9195/10000
1/1 [==============================] - 0s 105ms/step - loss: 2.3105e-06 - accuracy: 1.0000 - val_loss: 14.6819 - val_accuracy: 0.3154
Epoch 9196/10000
1/1 [==============================] - 0s 102ms/step - loss: 2.3105e-06 - accuracy: 1.0000 - val_loss: 14.6830 - val_accuracy: 0.3155
Epoch 9197/10000
1/1 [==============================] - 0s 104ms/step - loss: 2.3079e-06 - accuracy: 1.0000 - val_loss: 14.6843 - val_accuracy: 0.3154
Epoch 9198/10000
1/1 [==============================] - 0s 100ms/step - loss: 2.3057e-06 - accuracy: 1.0000 - val_loss: 14.6847 - val_accuracy: 0.3155
Epoch 9199/10000
1/1 [==============================] - 0s 106ms/step - loss: 2.3072e-06 - accuracy: 1.0000 - val_loss: 14.6847 - val_accuracy: 0.3154
Epoch 9200/10000
1/1 [==============================] - 0s 100ms/step - loss: 2.3065e-06 - accuracy: 1.0000 - val_loss: 14.6855 - val_accuracy: 0.3154
Epoch 9201/10000
1/1 [==============================] - 0s 103ms/step - loss: 2.3041e-06 - accuracy: 1.0000 - val_loss: 14.6862 - val_accuracy: 0.3154
Epoch 9202/10000
1/1 [==============================] - 0s 102ms/step - loss: 2.3014e-06 - accuracy: 1.0000 - val_loss: 14.6871 - val_accuracy: 0.3155
Epoch 9203/10000
1/1 [==============================] - 0s 105ms/step - loss: 2.3003e-06 - accuracy: 1.0000 - val_loss: 14.6879 - val_accuracy: 0.3155
Epoch 9204/10000
1/1 [==============================] - 0s 104ms/step - loss: 2.2993e-06 - accuracy: 1.0000 - val_loss: 14.6879 - val_accuracy: 0.3155
Epoch 9205/10000
1/1 [==============================] - 0s 104ms/step - loss: 2.2991e-06 - accuracy: 1.0000 - val_loss: 14.6879 - val_accuracy: 0.3154
Epoch 9206/10000
1/1 [==============================] - 0s 110ms/step - loss: 2.2974e-06 - accuracy: 1.0000 - val_loss: 14.6886 - val_accuracy: 0.3155
Epoch 9207/10000
1/1 [==============================] - 0s 105ms/step - loss: 2.2948e-06 - accuracy: 1.0000 - val_loss: 14.6900 - val_accuracy: 0.3156
Epoch 9208/10000
1/1 [==============================] - 0s 102ms/step - loss: 2.2938e-06 - accuracy: 1.0000 - val_loss: 14.6912 - val_accuracy: 0.3154
Epoch 9209/10000
1/1 [==============================] - 0s 107ms/step - loss: 2.2924e-06 - accuracy: 1.0000 - val_loss: 14.6913 - val_accuracy: 0.3155
Epoch 9210/10000
1/1 [==============================] - 0s 104ms/step - loss: 2.2926e-06 - accuracy: 1.0000 - val_loss: 14.6911 - val_accuracy: 0.3155
Epoch 9211/10000
1/1 [==============================] - 0s 101ms/step - loss: 2.2917e-06 - accuracy: 1.0000 - val_loss: 14.6918 - val_accuracy: 0.3154
Epoch 9212/10000
1/1 [==============================] - 0s 104ms/step - loss: 2.2888e-06 - accuracy: 1.0000 - val_loss: 14.6930 - val_accuracy: 0.3154
Epoch 9213/10000
1/1 [==============================] - 0s 104ms/step - loss: 2.2859e-06 - accuracy: 1.0000 - val_loss: 14.6935 - val_accuracy: 0.3154
Epoch 9214/10000
1/1 [==============================] - 0s 104ms/step - loss: 2.2845e-06 - accuracy: 1.0000 - val_loss: 14.6943 - val_accuracy: 0.3154
Epoch 9215/10000
1/1 [==============================] - 0s 104ms/step - loss: 2.2848e-06 - accuracy: 1.0000 - val_loss: 14.6947 - val_accuracy: 0.3154
Epoch 9216/10000
1/1 [==============================] - 0s 104ms/step - loss: 2.2814e-06 - accuracy: 1.0000 - val_loss: 14.6948 - val_accuracy: 0.3154
Epoch 9217/10000
1/1 [==============================] - 0s 109ms/step - loss: 2.2805e-06 - accuracy: 1.0000 - val_loss: 14.6947 - val_accuracy: 0.3154
Epoch 9218/10000
1/1 [==============================] - 0s 101ms/step - loss: 2.2800e-06 - accuracy: 1.0000 - val_loss: 14.6956 - val_accuracy: 0.3154
Epoch 9219/10000
1/1 [==============================] - 0s 100ms/step - loss: 2.2790e-06 - accuracy: 1.0000 - val_loss: 14.6970 - val_accuracy: 0.3156
Epoch 9220/10000
1/1 [==============================] - 0s 100ms/step - loss: 2.2771e-06 - accuracy: 1.0000 - val_loss: 14.6975 - val_accuracy: 0.3154
Epoch 9221/10000
1/1 [==============================] - 0s 104ms/step - loss: 2.2764e-06 - accuracy: 1.0000 - val_loss: 14.6974 - val_accuracy: 0.3154
Epoch 9222/10000
1/1 [==============================] - 0s 99ms/step - loss: 2.2747e-06 - accuracy: 1.0000 - val_loss: 14.6979 - val_accuracy: 0.3154
Epoch 9223/10000
1/1 [==============================] - 0s 104ms/step - loss: 2.2731e-06 - accuracy: 1.0000 - val_loss: 14.6991 - val_accuracy: 0.3155
Epoch 9224/10000
1/1 [==============================] - 0s 101ms/step - loss: 2.2695e-06 - accuracy: 1.0000 - val_loss: 14.6994 - val_accuracy: 0.3154
Epoch 9225/10000
1/1 [==============================] - 0s 103ms/step - loss: 2.2707e-06 - accuracy: 1.0000 - val_loss: 14.7000 - val_accuracy: 0.3154
Epoch 9226/10000
1/1 [==============================] - 0s 103ms/step - loss: 2.2683e-06 - accuracy: 1.0000 - val_loss: 14.7007 - val_accuracy: 0.3156
Epoch 9227/10000
1/1 [==============================] - 0s 104ms/step - loss: 2.2674e-06 - accuracy: 1.0000 - val_loss: 14.7013 - val_accuracy: 0.3156
Epoch 9228/10000
1/1 [==============================] - 0s 101ms/step - loss: 2.2674e-06 - accuracy: 1.0000 - val_loss: 14.7016 - val_accuracy: 0.3156
Epoch 9229/10000
1/1 [==============================] - 0s 107ms/step - loss: 2.2654e-06 - accuracy: 1.0000 - val_loss: 14.7020 - val_accuracy: 0.3154
Epoch 9230/10000
1/1 [==============================] - 0s 100ms/step - loss: 2.2628e-06 - accuracy: 1.0000 - val_loss: 14.7031 - val_accuracy: 0.3154
Epoch 9231/10000
1/1 [==============================] - 0s 99ms/step - loss: 2.2614e-06 - accuracy: 1.0000 - val_loss: 14.7037 - val_accuracy: 0.3156
Epoch 9232/10000
1/1 [==============================] - 0s 100ms/step - loss: 2.2607e-06 - accuracy: 1.0000 - val_loss: 14.7039 - val_accuracy: 0.3156
Epoch 9233/10000
1/1 [==============================] - 0s 99ms/step - loss: 2.2576e-06 - accuracy: 1.0000 - val_loss: 14.7046 - val_accuracy: 0.3155
Epoch 9234/10000
1/1 [==============================] - 0s 101ms/step - loss: 2.2576e-06 - accuracy: 1.0000 - val_loss: 14.7052 - val_accuracy: 0.3154
Epoch 9235/10000
1/1 [==============================] - 0s 102ms/step - loss: 2.2566e-06 - accuracy: 1.0000 - val_loss: 14.7059 - val_accuracy: 0.3155
Epoch 9236/10000
1/1 [==============================] - 0s 101ms/step - loss: 2.2554e-06 - accuracy: 1.0000 - val_loss: 14.7065 - val_accuracy: 0.3155
Epoch 9237/10000
1/1 [==============================] - 0s 101ms/step - loss: 2.2542e-06 - accuracy: 1.0000 - val_loss: 14.7067 - val_accuracy: 0.3154
Epoch 9238/10000
1/1 [==============================] - 0s 107ms/step - loss: 2.2530e-06 - accuracy: 1.0000 - val_loss: 14.7069 - val_accuracy: 0.3154
Epoch 9239/10000
1/1 [==============================] - 0s 103ms/step - loss: 2.2507e-06 - accuracy: 1.0000 - val_loss: 14.7066 - val_accuracy: 0.3155
Epoch 9240/10000
1/1 [==============================] - 0s 103ms/step - loss: 2.2488e-06 - accuracy: 1.0000 - val_loss: 14.7073 - val_accuracy: 0.3156
Epoch 9241/10000
1/1 [==============================] - 0s 102ms/step - loss: 2.2476e-06 - accuracy: 1.0000 - val_loss: 14.7086 - val_accuracy: 0.3156
Epoch 9242/10000
1/1 [==============================] - 0s 102ms/step - loss: 2.2480e-06 - accuracy: 1.0000 - val_loss: 14.7096 - val_accuracy: 0.3156
Epoch 9243/10000
1/1 [==============================] - 0s 107ms/step - loss: 2.2437e-06 - accuracy: 1.0000 - val_loss: 14.7104 - val_accuracy: 0.3155
Epoch 9244/10000
1/1 [==============================] - 0s 103ms/step - loss: 2.2433e-06 - accuracy: 1.0000 - val_loss: 14.7109 - val_accuracy: 0.3154
Epoch 9245/10000
1/1 [==============================] - 0s 106ms/step - loss: 2.2447e-06 - accuracy: 1.0000 - val_loss: 14.7114 - val_accuracy: 0.3154
Epoch 9246/10000
1/1 [==============================] - 0s 101ms/step - loss: 2.2423e-06 - accuracy: 1.0000 - val_loss: 14.7127 - val_accuracy: 0.3155
Epoch 9247/10000
1/1 [==============================] - 0s 102ms/step - loss: 2.2402e-06 - accuracy: 1.0000 - val_loss: 14.7130 - val_accuracy: 0.3155
Epoch 9248/10000
1/1 [==============================] - 0s 110ms/step - loss: 2.2383e-06 - accuracy: 1.0000 - val_loss: 14.7129 - val_accuracy: 0.3154
Epoch 9249/10000
1/1 [==============================] - 0s 109ms/step - loss: 2.2378e-06 - accuracy: 1.0000 - val_loss: 14.7136 - val_accuracy: 0.3154
Epoch 9250/10000
1/1 [==============================] - 0s 105ms/step - loss: 2.2345e-06 - accuracy: 1.0000 - val_loss: 14.7149 - val_accuracy: 0.3154
Epoch 9251/10000
1/1 [==============================] - 0s 115ms/step - loss: 2.2349e-06 - accuracy: 1.0000 - val_loss: 14.7155 - val_accuracy: 0.3155
Epoch 9252/10000
1/1 [==============================] - 0s 110ms/step - loss: 2.2347e-06 - accuracy: 1.0000 - val_loss: 14.7152 - val_accuracy: 0.3154
Epoch 9253/10000
1/1 [==============================] - 0s 106ms/step - loss: 2.2340e-06 - accuracy: 1.0000 - val_loss: 14.7153 - val_accuracy: 0.3155
Epoch 9254/10000
1/1 [==============================] - 0s 102ms/step - loss: 2.2316e-06 - accuracy: 1.0000 - val_loss: 14.7160 - val_accuracy: 0.3154
Epoch 9255/10000
1/1 [==============================] - 0s 106ms/step - loss: 2.2299e-06 - accuracy: 1.0000 - val_loss: 14.7169 - val_accuracy: 0.3154
Epoch 9256/10000
1/1 [==============================] - 0s 105ms/step - loss: 2.2294e-06 - accuracy: 1.0000 - val_loss: 14.7184 - val_accuracy: 0.3154
Epoch 9257/10000
1/1 [==============================] - 0s 101ms/step - loss: 2.2299e-06 - accuracy: 1.0000 - val_loss: 14.7189 - val_accuracy: 0.3155
Epoch 9258/10000
1/1 [==============================] - 0s 107ms/step - loss: 2.2271e-06 - accuracy: 1.0000 - val_loss: 14.7187 - val_accuracy: 0.3155
Epoch 9259/10000
1/1 [==============================] - 0s 103ms/step - loss: 2.2252e-06 - accuracy: 1.0000 - val_loss: 14.7187 - val_accuracy: 0.3154
Epoch 9260/10000
1/1 [==============================] - 0s 103ms/step - loss: 2.2261e-06 - accuracy: 1.0000 - val_loss: 14.7200 - val_accuracy: 0.3154
Epoch 9261/10000
1/1 [==============================] - 0s 102ms/step - loss: 2.2249e-06 - accuracy: 1.0000 - val_loss: 14.7216 - val_accuracy: 0.3155
Epoch 9262/10000
1/1 [==============================] - 0s 103ms/step - loss: 2.2221e-06 - accuracy: 1.0000 - val_loss: 14.7217 - val_accuracy: 0.3155
Epoch 9263/10000
1/1 [==============================] - 0s 102ms/step - loss: 2.2221e-06 - accuracy: 1.0000 - val_loss: 14.7213 - val_accuracy: 0.3154
Epoch 9264/10000
1/1 [==============================] - 0s 103ms/step - loss: 2.2204e-06 - accuracy: 1.0000 - val_loss: 14.7213 - val_accuracy: 0.3155
Epoch 9265/10000
1/1 [==============================] - 0s 104ms/step - loss: 2.2197e-06 - accuracy: 1.0000 - val_loss: 14.7224 - val_accuracy: 0.3154
Epoch 9266/10000
1/1 [==============================] - 0s 110ms/step - loss: 2.2173e-06 - accuracy: 1.0000 - val_loss: 14.7238 - val_accuracy: 0.3153
Epoch 9267/10000
1/1 [==============================] - 0s 102ms/step - loss: 2.2139e-06 - accuracy: 1.0000 - val_loss: 14.7248 - val_accuracy: 0.3154
Epoch 9268/10000
1/1 [==============================] - 0s 101ms/step - loss: 2.2149e-06 - accuracy: 1.0000 - val_loss: 14.7248 - val_accuracy: 0.3154
Epoch 9269/10000
1/1 [==============================] - 0s 100ms/step - loss: 2.2135e-06 - accuracy: 1.0000 - val_loss: 14.7244 - val_accuracy: 0.3155
Epoch 9270/10000
1/1 [==============================] - 0s 106ms/step - loss: 2.2120e-06 - accuracy: 1.0000 - val_loss: 14.7246 - val_accuracy: 0.3154
Epoch 9271/10000
1/1 [==============================] - 0s 101ms/step - loss: 2.2108e-06 - accuracy: 1.0000 - val_loss: 14.7259 - val_accuracy: 0.3154
Epoch 9272/10000
1/1 [==============================] - 0s 103ms/step - loss: 2.2094e-06 - accuracy: 1.0000 - val_loss: 14.7279 - val_accuracy: 0.3154
Epoch 9273/10000
1/1 [==============================] - 0s 102ms/step - loss: 2.2099e-06 - accuracy: 1.0000 - val_loss: 14.7285 - val_accuracy: 0.3153
Epoch 9274/10000
1/1 [==============================] - 0s 105ms/step - loss: 2.2082e-06 - accuracy: 1.0000 - val_loss: 14.7281 - val_accuracy: 0.3153
Epoch 9275/10000
1/1 [==============================] - 0s 103ms/step - loss: 2.2066e-06 - accuracy: 1.0000 - val_loss: 14.7280 - val_accuracy: 0.3153
Epoch 9276/10000
1/1 [==============================] - 0s 102ms/step - loss: 2.2037e-06 - accuracy: 1.0000 - val_loss: 14.7287 - val_accuracy: 0.3155
Epoch 9277/10000
1/1 [==============================] - 0s 99ms/step - loss: 2.2037e-06 - accuracy: 1.0000 - val_loss: 14.7299 - val_accuracy: 0.3153
Epoch 9278/10000
1/1 [==============================] - 0s 104ms/step - loss: 2.2023e-06 - accuracy: 1.0000 - val_loss: 14.7310 - val_accuracy: 0.3153
Epoch 9279/10000
1/1 [==============================] - 0s 102ms/step - loss: 2.2020e-06 - accuracy: 1.0000 - val_loss: 14.7318 - val_accuracy: 0.3154
Epoch 9280/10000
1/1 [==============================] - 0s 107ms/step - loss: 2.2001e-06 - accuracy: 1.0000 - val_loss: 14.7315 - val_accuracy: 0.3153
Epoch 9281/10000
1/1 [==============================] - 0s 102ms/step - loss: 2.1965e-06 - accuracy: 1.0000 - val_loss: 14.7310 - val_accuracy: 0.3153
Epoch 9282/10000
1/1 [==============================] - 0s 102ms/step - loss: 2.1965e-06 - accuracy: 1.0000 - val_loss: 14.7310 - val_accuracy: 0.3153
Epoch 9283/10000
1/1 [==============================] - 0s 105ms/step - loss: 2.1942e-06 - accuracy: 1.0000 - val_loss: 14.7320 - val_accuracy: 0.3154
Epoch 9284/10000
1/1 [==============================] - 0s 107ms/step - loss: 2.1939e-06 - accuracy: 1.0000 - val_loss: 14.7330 - val_accuracy: 0.3153
Epoch 9285/10000
1/1 [==============================] - 0s 100ms/step - loss: 2.1930e-06 - accuracy: 1.0000 - val_loss: 14.7340 - val_accuracy: 0.3153
Epoch 9286/10000
1/1 [==============================] - 0s 108ms/step - loss: 2.1896e-06 - accuracy: 1.0000 - val_loss: 14.7355 - val_accuracy: 0.3153
Epoch 9287/10000
1/1 [==============================] - 0s 107ms/step - loss: 2.1887e-06 - accuracy: 1.0000 - val_loss: 14.7363 - val_accuracy: 0.3153
Epoch 9288/10000
1/1 [==============================] - 0s 102ms/step - loss: 2.1896e-06 - accuracy: 1.0000 - val_loss: 14.7366 - val_accuracy: 0.3153
Epoch 9289/10000
1/1 [==============================] - 0s 102ms/step - loss: 2.1894e-06 - accuracy: 1.0000 - val_loss: 14.7368 - val_accuracy: 0.3154
Epoch 9290/10000
1/1 [==============================] - 0s 104ms/step - loss: 2.1858e-06 - accuracy: 1.0000 - val_loss: 14.7371 - val_accuracy: 0.3154
Epoch 9291/10000
1/1 [==============================] - 0s 104ms/step - loss: 2.1841e-06 - accuracy: 1.0000 - val_loss: 14.7376 - val_accuracy: 0.3154
Epoch 9292/10000
1/1 [==============================] - 0s 108ms/step - loss: 2.1830e-06 - accuracy: 1.0000 - val_loss: 14.7383 - val_accuracy: 0.3153
Epoch 9293/10000
1/1 [==============================] - 0s 100ms/step - loss: 2.1820e-06 - accuracy: 1.0000 - val_loss: 14.7390 - val_accuracy: 0.3153
Epoch 9294/10000
1/1 [==============================] - 0s 103ms/step - loss: 2.1794e-06 - accuracy: 1.0000 - val_loss: 14.7396 - val_accuracy: 0.3153
Epoch 9295/10000
1/1 [==============================] - 0s 105ms/step - loss: 2.1801e-06 - accuracy: 1.0000 - val_loss: 14.7400 - val_accuracy: 0.3153
Epoch 9296/10000
1/1 [==============================] - 0s 105ms/step - loss: 2.1794e-06 - accuracy: 1.0000 - val_loss: 14.7407 - val_accuracy: 0.3155
Epoch 9297/10000
1/1 [==============================] - 0s 104ms/step - loss: 2.1784e-06 - accuracy: 1.0000 - val_loss: 14.7413 - val_accuracy: 0.3154
Epoch 9298/10000
1/1 [==============================] - 0s 105ms/step - loss: 2.1758e-06 - accuracy: 1.0000 - val_loss: 14.7419 - val_accuracy: 0.3152
Epoch 9299/10000
1/1 [==============================] - 0s 103ms/step - loss: 2.1753e-06 - accuracy: 1.0000 - val_loss: 14.7427 - val_accuracy: 0.3152
Epoch 9300/10000
1/1 [==============================] - 0s 103ms/step - loss: 2.1748e-06 - accuracy: 1.0000 - val_loss: 14.7431 - val_accuracy: 0.3152
Epoch 9301/10000
1/1 [==============================] - 0s 100ms/step - loss: 2.1729e-06 - accuracy: 1.0000 - val_loss: 14.7436 - val_accuracy: 0.3153
Epoch 9302/10000
1/1 [==============================] - 0s 99ms/step - loss: 2.1717e-06 - accuracy: 1.0000 - val_loss: 14.7441 - val_accuracy: 0.3154
Epoch 9303/10000
1/1 [==============================] - 0s 100ms/step - loss: 2.1698e-06 - accuracy: 1.0000 - val_loss: 14.7448 - val_accuracy: 0.3153
Epoch 9304/10000
1/1 [==============================] - 0s 100ms/step - loss: 2.1691e-06 - accuracy: 1.0000 - val_loss: 14.7454 - val_accuracy: 0.3153
Epoch 9305/10000
1/1 [==============================] - 0s 101ms/step - loss: 2.1672e-06 - accuracy: 1.0000 - val_loss: 14.7458 - val_accuracy: 0.3153
Epoch 9306/10000
1/1 [==============================] - 0s 104ms/step - loss: 2.1667e-06 - accuracy: 1.0000 - val_loss: 14.7453 - val_accuracy: 0.3153
Epoch 9307/10000
1/1 [==============================] - 0s 103ms/step - loss: 2.1639e-06 - accuracy: 1.0000 - val_loss: 14.7455 - val_accuracy: 0.3152
Epoch 9308/10000
1/1 [==============================] - 0s 107ms/step - loss: 2.1646e-06 - accuracy: 1.0000 - val_loss: 14.7466 - val_accuracy: 0.3153
Epoch 9309/10000
1/1 [==============================] - 0s 100ms/step - loss: 2.1622e-06 - accuracy: 1.0000 - val_loss: 14.7486 - val_accuracy: 0.3152
Epoch 9310/10000
1/1 [==============================] - 0s 105ms/step - loss: 2.1624e-06 - accuracy: 1.0000 - val_loss: 14.7491 - val_accuracy: 0.3153
Epoch 9311/10000
1/1 [==============================] - 0s 103ms/step - loss: 2.1615e-06 - accuracy: 1.0000 - val_loss: 14.7490 - val_accuracy: 0.3151
Epoch 9312/10000
1/1 [==============================] - 0s 105ms/step - loss: 2.1563e-06 - accuracy: 1.0000 - val_loss: 14.7494 - val_accuracy: 0.3153
Epoch 9313/10000
1/1 [==============================] - 0s 109ms/step - loss: 2.1560e-06 - accuracy: 1.0000 - val_loss: 14.7508 - val_accuracy: 0.3153
Epoch 9314/10000
1/1 [==============================] - 0s 101ms/step - loss: 2.1555e-06 - accuracy: 1.0000 - val_loss: 14.7523 - val_accuracy: 0.3152
Epoch 9315/10000
1/1 [==============================] - 0s 103ms/step - loss: 2.1567e-06 - accuracy: 1.0000 - val_loss: 14.7526 - val_accuracy: 0.3152
Epoch 9316/10000
1/1 [==============================] - 0s 102ms/step - loss: 2.1555e-06 - accuracy: 1.0000 - val_loss: 14.7520 - val_accuracy: 0.3153
Epoch 9317/10000
1/1 [==============================] - 0s 100ms/step - loss: 2.1532e-06 - accuracy: 1.0000 - val_loss: 14.7516 - val_accuracy: 0.3153
Epoch 9318/10000
1/1 [==============================] - 0s 100ms/step - loss: 2.1508e-06 - accuracy: 1.0000 - val_loss: 14.7522 - val_accuracy: 0.3153
Epoch 9319/10000
1/1 [==============================] - 0s 99ms/step - loss: 2.1486e-06 - accuracy: 1.0000 - val_loss: 14.7535 - val_accuracy: 0.3152
Epoch 9320/10000
1/1 [==============================] - 0s 101ms/step - loss: 2.1474e-06 - accuracy: 1.0000 - val_loss: 14.7548 - val_accuracy: 0.3152
Epoch 9321/10000
1/1 [==============================] - 0s 113ms/step - loss: 2.1470e-06 - accuracy: 1.0000 - val_loss: 14.7559 - val_accuracy: 0.3152
Epoch 9322/10000
1/1 [==============================] - 0s 101ms/step - loss: 2.1448e-06 - accuracy: 1.0000 - val_loss: 14.7556 - val_accuracy: 0.3151
Epoch 9323/10000
1/1 [==============================] - 0s 108ms/step - loss: 2.1443e-06 - accuracy: 1.0000 - val_loss: 14.7554 - val_accuracy: 0.3151
Epoch 9324/10000
1/1 [==============================] - 0s 106ms/step - loss: 2.1431e-06 - accuracy: 1.0000 - val_loss: 14.7557 - val_accuracy: 0.3151
Epoch 9325/10000
1/1 [==============================] - 0s 110ms/step - loss: 2.1412e-06 - accuracy: 1.0000 - val_loss: 14.7569 - val_accuracy: 0.3151
Epoch 9326/10000
1/1 [==============================] - 0s 102ms/step - loss: 2.1403e-06 - accuracy: 1.0000 - val_loss: 14.7581 - val_accuracy: 0.3152
Epoch 9327/10000
1/1 [==============================] - 0s 108ms/step - loss: 2.1388e-06 - accuracy: 1.0000 - val_loss: 14.7590 - val_accuracy: 0.3153
Epoch 9328/10000
1/1 [==============================] - 0s 100ms/step - loss: 2.1379e-06 - accuracy: 1.0000 - val_loss: 14.7591 - val_accuracy: 0.3151
Epoch 9329/10000
1/1 [==============================] - 0s 101ms/step - loss: 2.1362e-06 - accuracy: 1.0000 - val_loss: 14.7593 - val_accuracy: 0.3151
Epoch 9330/10000
1/1 [==============================] - 0s 105ms/step - loss: 2.1357e-06 - accuracy: 1.0000 - val_loss: 14.7600 - val_accuracy: 0.3151
Epoch 9331/10000
1/1 [==============================] - 0s 104ms/step - loss: 2.1350e-06 - accuracy: 1.0000 - val_loss: 14.7613 - val_accuracy: 0.3151
Epoch 9332/10000
1/1 [==============================] - 0s 105ms/step - loss: 2.1315e-06 - accuracy: 1.0000 - val_loss: 14.7622 - val_accuracy: 0.3151
Epoch 9333/10000
1/1 [==============================] - 0s 100ms/step - loss: 2.1288e-06 - accuracy: 1.0000 - val_loss: 14.7622 - val_accuracy: 0.3151
Epoch 9334/10000
1/1 [==============================] - 0s 99ms/step - loss: 2.1286e-06 - accuracy: 1.0000 - val_loss: 14.7621 - val_accuracy: 0.3150
Epoch 9335/10000
1/1 [==============================] - 0s 104ms/step - loss: 2.1279e-06 - accuracy: 1.0000 - val_loss: 14.7623 - val_accuracy: 0.3150
Epoch 9336/10000
1/1 [==============================] - 0s 105ms/step - loss: 2.1281e-06 - accuracy: 1.0000 - val_loss: 14.7636 - val_accuracy: 0.3152
Epoch 9337/10000
1/1 [==============================] - 0s 98ms/step - loss: 2.1257e-06 - accuracy: 1.0000 - val_loss: 14.7651 - val_accuracy: 0.3152
Epoch 9338/10000
1/1 [==============================] - 0s 101ms/step - loss: 2.1257e-06 - accuracy: 1.0000 - val_loss: 14.7651 - val_accuracy: 0.3151
Epoch 9339/10000
1/1 [==============================] - 0s 105ms/step - loss: 2.1243e-06 - accuracy: 1.0000 - val_loss: 14.7650 - val_accuracy: 0.3151
Epoch 9340/10000
1/1 [==============================] - 0s 101ms/step - loss: 2.1222e-06 - accuracy: 1.0000 - val_loss: 14.7654 - val_accuracy: 0.3151
Epoch 9341/10000
1/1 [==============================] - 0s 102ms/step - loss: 2.1212e-06 - accuracy: 1.0000 - val_loss: 14.7664 - val_accuracy: 0.3151
Epoch 9342/10000
1/1 [==============================] - 0s 102ms/step - loss: 2.1200e-06 - accuracy: 1.0000 - val_loss: 14.7678 - val_accuracy: 0.3152
Epoch 9343/10000
1/1 [==============================] - 0s 102ms/step - loss: 2.1195e-06 - accuracy: 1.0000 - val_loss: 14.7681 - val_accuracy: 0.3151
Epoch 9344/10000
1/1 [==============================] - 0s 101ms/step - loss: 2.1198e-06 - accuracy: 1.0000 - val_loss: 14.7683 - val_accuracy: 0.3151
Epoch 9345/10000
1/1 [==============================] - 0s 102ms/step - loss: 2.1176e-06 - accuracy: 1.0000 - val_loss: 14.7685 - val_accuracy: 0.3151
Epoch 9346/10000
1/1 [==============================] - 0s 98ms/step - loss: 2.1152e-06 - accuracy: 1.0000 - val_loss: 14.7691 - val_accuracy: 0.3152
Epoch 9347/10000
1/1 [==============================] - 0s 101ms/step - loss: 2.1148e-06 - accuracy: 1.0000 - val_loss: 14.7701 - val_accuracy: 0.3151
Epoch 9348/10000
1/1 [==============================] - 0s 107ms/step - loss: 2.1126e-06 - accuracy: 1.0000 - val_loss: 14.7709 - val_accuracy: 0.3151
Epoch 9349/10000
1/1 [==============================] - 0s 103ms/step - loss: 2.1119e-06 - accuracy: 1.0000 - val_loss: 14.7711 - val_accuracy: 0.3151
Epoch 9350/10000
1/1 [==============================] - 0s 101ms/step - loss: 2.1114e-06 - accuracy: 1.0000 - val_loss: 14.7714 - val_accuracy: 0.3151
Epoch 9351/10000
1/1 [==============================] - 0s 105ms/step - loss: 2.1100e-06 - accuracy: 1.0000 - val_loss: 14.7722 - val_accuracy: 0.3150
Epoch 9352/10000
1/1 [==============================] - 0s 101ms/step - loss: 2.1083e-06 - accuracy: 1.0000 - val_loss: 14.7731 - val_accuracy: 0.3151
Epoch 9353/10000
1/1 [==============================] - 0s 98ms/step - loss: 2.1074e-06 - accuracy: 1.0000 - val_loss: 14.7739 - val_accuracy: 0.3152
Epoch 9354/10000
1/1 [==============================] - 0s 105ms/step - loss: 2.1062e-06 - accuracy: 1.0000 - val_loss: 14.7741 - val_accuracy: 0.3151
Epoch 9355/10000
1/1 [==============================] - 0s 104ms/step - loss: 2.1059e-06 - accuracy: 1.0000 - val_loss: 14.7744 - val_accuracy: 0.3151
Epoch 9356/10000
1/1 [==============================] - 0s 99ms/step - loss: 2.1040e-06 - accuracy: 1.0000 - val_loss: 14.7753 - val_accuracy: 0.3150
Epoch 9357/10000
1/1 [==============================] - 0s 102ms/step - loss: 2.1028e-06 - accuracy: 1.0000 - val_loss: 14.7763 - val_accuracy: 0.3151
Epoch 9358/10000
1/1 [==============================] - 0s 106ms/step - loss: 2.1014e-06 - accuracy: 1.0000 - val_loss: 14.7768 - val_accuracy: 0.3151
Epoch 9359/10000
1/1 [==============================] - 0s 102ms/step - loss: 2.1007e-06 - accuracy: 1.0000 - val_loss: 14.7771 - val_accuracy: 0.3151
Epoch 9360/10000
1/1 [==============================] - 0s 101ms/step - loss: 2.0974e-06 - accuracy: 1.0000 - val_loss: 14.7777 - val_accuracy: 0.3150
Epoch 9361/10000
1/1 [==============================] - 0s 112ms/step - loss: 2.0978e-06 - accuracy: 1.0000 - val_loss: 14.7779 - val_accuracy: 0.3151
Epoch 9362/10000
1/1 [==============================] - 0s 103ms/step - loss: 2.0969e-06 - accuracy: 1.0000 - val_loss: 14.7788 - val_accuracy: 0.3152
Epoch 9363/10000
1/1 [==============================] - 0s 107ms/step - loss: 2.0955e-06 - accuracy: 1.0000 - val_loss: 14.7791 - val_accuracy: 0.3151
Epoch 9364/10000
1/1 [==============================] - 0s 120ms/step - loss: 2.0938e-06 - accuracy: 1.0000 - val_loss: 14.7790 - val_accuracy: 0.3151
Epoch 9365/10000
1/1 [==============================] - 0s 107ms/step - loss: 2.0943e-06 - accuracy: 1.0000 - val_loss: 14.7793 - val_accuracy: 0.3151
Epoch 9366/10000
1/1 [==============================] - 0s 103ms/step - loss: 2.0938e-06 - accuracy: 1.0000 - val_loss: 14.7806 - val_accuracy: 0.3151
Epoch 9367/10000
1/1 [==============================] - 0s 105ms/step - loss: 2.0907e-06 - accuracy: 1.0000 - val_loss: 14.7819 - val_accuracy: 0.3151
Epoch 9368/10000
1/1 [==============================] - 0s 107ms/step - loss: 2.0881e-06 - accuracy: 1.0000 - val_loss: 14.7829 - val_accuracy: 0.3151
Epoch 9369/10000
1/1 [==============================] - 0s 104ms/step - loss: 2.0885e-06 - accuracy: 1.0000 - val_loss: 14.7827 - val_accuracy: 0.3151
Epoch 9370/10000
1/1 [==============================] - 0s 104ms/step - loss: 2.0876e-06 - accuracy: 1.0000 - val_loss: 14.7826 - val_accuracy: 0.3151
Epoch 9371/10000
1/1 [==============================] - 0s 105ms/step - loss: 2.0864e-06 - accuracy: 1.0000 - val_loss: 14.7833 - val_accuracy: 0.3151
Epoch 9372/10000
1/1 [==============================] - 0s 109ms/step - loss: 2.0850e-06 - accuracy: 1.0000 - val_loss: 14.7843 - val_accuracy: 0.3151
Epoch 9373/10000
1/1 [==============================] - 0s 101ms/step - loss: 2.0838e-06 - accuracy: 1.0000 - val_loss: 14.7851 - val_accuracy: 0.3152
Epoch 9374/10000
1/1 [==============================] - 0s 104ms/step - loss: 2.0835e-06 - accuracy: 1.0000 - val_loss: 14.7862 - val_accuracy: 0.3151
Epoch 9375/10000
1/1 [==============================] - 0s 107ms/step - loss: 2.0811e-06 - accuracy: 1.0000 - val_loss: 14.7867 - val_accuracy: 0.3151
Epoch 9376/10000
1/1 [==============================] - 0s 106ms/step - loss: 2.0790e-06 - accuracy: 1.0000 - val_loss: 14.7868 - val_accuracy: 0.3151
Epoch 9377/10000
1/1 [==============================] - 0s 104ms/step - loss: 2.0778e-06 - accuracy: 1.0000 - val_loss: 14.7874 - val_accuracy: 0.3151
Epoch 9378/10000
1/1 [==============================] - 0s 105ms/step - loss: 2.0766e-06 - accuracy: 1.0000 - val_loss: 14.7878 - val_accuracy: 0.3151
Epoch 9379/10000
1/1 [==============================] - 0s 112ms/step - loss: 2.0764e-06 - accuracy: 1.0000 - val_loss: 14.7883 - val_accuracy: 0.3151
Epoch 9380/10000
1/1 [==============================] - 0s 107ms/step - loss: 2.0752e-06 - accuracy: 1.0000 - val_loss: 14.7888 - val_accuracy: 0.3151
Epoch 9381/10000
1/1 [==============================] - 0s 110ms/step - loss: 2.0750e-06 - accuracy: 1.0000 - val_loss: 14.7894 - val_accuracy: 0.3151
Epoch 9382/10000
1/1 [==============================] - 0s 113ms/step - loss: 2.0721e-06 - accuracy: 1.0000 - val_loss: 14.7900 - val_accuracy: 0.3152
Epoch 9383/10000
1/1 [==============================] - 0s 108ms/step - loss: 2.0714e-06 - accuracy: 1.0000 - val_loss: 14.7907 - val_accuracy: 0.3152
Epoch 9384/10000
1/1 [==============================] - 0s 101ms/step - loss: 2.0697e-06 - accuracy: 1.0000 - val_loss: 14.7913 - val_accuracy: 0.3151
Epoch 9385/10000
1/1 [==============================] - 0s 103ms/step - loss: 2.0676e-06 - accuracy: 1.0000 - val_loss: 14.7917 - val_accuracy: 0.3151
Epoch 9386/10000
1/1 [==============================] - 0s 105ms/step - loss: 2.0683e-06 - accuracy: 1.0000 - val_loss: 14.7918 - val_accuracy: 0.3151
Epoch 9387/10000
1/1 [==============================] - 0s 100ms/step - loss: 2.0678e-06 - accuracy: 1.0000 - val_loss: 14.7928 - val_accuracy: 0.3151
Epoch 9388/10000
1/1 [==============================] - 0s 106ms/step - loss: 2.0664e-06 - accuracy: 1.0000 - val_loss: 14.7944 - val_accuracy: 0.3151
Epoch 9389/10000
1/1 [==============================] - 0s 100ms/step - loss: 2.0637e-06 - accuracy: 1.0000 - val_loss: 14.7944 - val_accuracy: 0.3151
Epoch 9390/10000
1/1 [==============================] - 0s 101ms/step - loss: 2.0635e-06 - accuracy: 1.0000 - val_loss: 14.7938 - val_accuracy: 0.3152
Epoch 9391/10000
1/1 [==============================] - 0s 105ms/step - loss: 2.0614e-06 - accuracy: 1.0000 - val_loss: 14.7944 - val_accuracy: 0.3151
Epoch 9392/10000
1/1 [==============================] - 0s 104ms/step - loss: 2.0609e-06 - accuracy: 1.0000 - val_loss: 14.7962 - val_accuracy: 0.3152
Epoch 9393/10000
1/1 [==============================] - 0s 104ms/step - loss: 2.0604e-06 - accuracy: 1.0000 - val_loss: 14.7975 - val_accuracy: 0.3151
Epoch 9394/10000
1/1 [==============================] - 0s 100ms/step - loss: 2.0580e-06 - accuracy: 1.0000 - val_loss: 14.7975 - val_accuracy: 0.3151
Epoch 9395/10000
1/1 [==============================] - 0s 101ms/step - loss: 2.0580e-06 - accuracy: 1.0000 - val_loss: 14.7971 - val_accuracy: 0.3151
Epoch 9396/10000
1/1 [==============================] - 0s 101ms/step - loss: 2.0571e-06 - accuracy: 1.0000 - val_loss: 14.7976 - val_accuracy: 0.3152
Epoch 9397/10000
1/1 [==============================] - 0s 105ms/step - loss: 2.0561e-06 - accuracy: 1.0000 - val_loss: 14.7990 - val_accuracy: 0.3152
Epoch 9398/10000
1/1 [==============================] - 0s 107ms/step - loss: 2.0559e-06 - accuracy: 1.0000 - val_loss: 14.8001 - val_accuracy: 0.3152
Epoch 9399/10000
1/1 [==============================] - 0s 102ms/step - loss: 2.0547e-06 - accuracy: 1.0000 - val_loss: 14.8001 - val_accuracy: 0.3151
Epoch 9400/10000
1/1 [==============================] - 0s 104ms/step - loss: 2.0528e-06 - accuracy: 1.0000 - val_loss: 14.7998 - val_accuracy: 0.3152
Epoch 9401/10000
1/1 [==============================] - 0s 107ms/step - loss: 2.0504e-06 - accuracy: 1.0000 - val_loss: 14.8006 - val_accuracy: 0.3152
Epoch 9402/10000
1/1 [==============================] - 0s 102ms/step - loss: 2.0490e-06 - accuracy: 1.0000 - val_loss: 14.8018 - val_accuracy: 0.3152
Epoch 9403/10000
1/1 [==============================] - 0s 99ms/step - loss: 2.0473e-06 - accuracy: 1.0000 - val_loss: 14.8028 - val_accuracy: 0.3152
Epoch 9404/10000
1/1 [==============================] - 0s 100ms/step - loss: 2.0463e-06 - accuracy: 1.0000 - val_loss: 14.8031 - val_accuracy: 0.3150
Epoch 9405/10000
1/1 [==============================] - 0s 102ms/step - loss: 2.0456e-06 - accuracy: 1.0000 - val_loss: 14.8034 - val_accuracy: 0.3152
Epoch 9406/10000
1/1 [==============================] - 0s 107ms/step - loss: 2.0449e-06 - accuracy: 1.0000 - val_loss: 14.8037 - val_accuracy: 0.3152
Epoch 9407/10000
1/1 [==============================] - 0s 106ms/step - loss: 2.0425e-06 - accuracy: 1.0000 - val_loss: 14.8042 - val_accuracy: 0.3152
Epoch 9408/10000
1/1 [==============================] - 0s 107ms/step - loss: 2.0416e-06 - accuracy: 1.0000 - val_loss: 14.8050 - val_accuracy: 0.3152
Epoch 9409/10000
1/1 [==============================] - 0s 101ms/step - loss: 2.0416e-06 - accuracy: 1.0000 - val_loss: 14.8063 - val_accuracy: 0.3151
Epoch 9410/10000
1/1 [==============================] - 0s 102ms/step - loss: 2.0397e-06 - accuracy: 1.0000 - val_loss: 14.8068 - val_accuracy: 0.3152
Epoch 9411/10000
1/1 [==============================] - 0s 104ms/step - loss: 2.0392e-06 - accuracy: 1.0000 - val_loss: 14.8069 - val_accuracy: 0.3152
Epoch 9412/10000
1/1 [==============================] - 0s 100ms/step - loss: 2.0370e-06 - accuracy: 1.0000 - val_loss: 14.8068 - val_accuracy: 0.3152
Epoch 9413/10000
1/1 [==============================] - 0s 101ms/step - loss: 2.0361e-06 - accuracy: 1.0000 - val_loss: 14.8070 - val_accuracy: 0.3152
Epoch 9414/10000
1/1 [==============================] - 0s 100ms/step - loss: 2.0351e-06 - accuracy: 1.0000 - val_loss: 14.8079 - val_accuracy: 0.3151
Epoch 9415/10000
1/1 [==============================] - 0s 101ms/step - loss: 2.0339e-06 - accuracy: 1.0000 - val_loss: 14.8091 - val_accuracy: 0.3152
Epoch 9416/10000
1/1 [==============================] - 0s 105ms/step - loss: 2.0344e-06 - accuracy: 1.0000 - val_loss: 14.8101 - val_accuracy: 0.3152
Epoch 9417/10000
1/1 [==============================] - 0s 104ms/step - loss: 2.0330e-06 - accuracy: 1.0000 - val_loss: 14.8105 - val_accuracy: 0.3152
Epoch 9418/10000
1/1 [==============================] - 0s 110ms/step - loss: 2.0320e-06 - accuracy: 1.0000 - val_loss: 14.8105 - val_accuracy: 0.3152
Epoch 9419/10000
1/1 [==============================] - 0s 101ms/step - loss: 2.0289e-06 - accuracy: 1.0000 - val_loss: 14.8111 - val_accuracy: 0.3152
Epoch 9420/10000
1/1 [==============================] - 0s 107ms/step - loss: 2.0280e-06 - accuracy: 1.0000 - val_loss: 14.8121 - val_accuracy: 0.3152
Epoch 9421/10000
1/1 [==============================] - 0s 103ms/step - loss: 2.0282e-06 - accuracy: 1.0000 - val_loss: 14.8129 - val_accuracy: 0.3152
Epoch 9422/10000
1/1 [==============================] - 0s 104ms/step - loss: 2.0268e-06 - accuracy: 1.0000 - val_loss: 14.8129 - val_accuracy: 0.3152
Epoch 9423/10000
1/1 [==============================] - 0s 104ms/step - loss: 2.0249e-06 - accuracy: 1.0000 - val_loss: 14.8134 - val_accuracy: 0.3152
Epoch 9424/10000
1/1 [==============================] - 0s 105ms/step - loss: 2.0246e-06 - accuracy: 1.0000 - val_loss: 14.8145 - val_accuracy: 0.3152
Epoch 9425/10000
1/1 [==============================] - 0s 102ms/step - loss: 2.0244e-06 - accuracy: 1.0000 - val_loss: 14.8148 - val_accuracy: 0.3152
Epoch 9426/10000
1/1 [==============================] - 0s 102ms/step - loss: 2.0237e-06 - accuracy: 1.0000 - val_loss: 14.8147 - val_accuracy: 0.3152
Epoch 9427/10000
1/1 [==============================] - 0s 100ms/step - loss: 2.0225e-06 - accuracy: 1.0000 - val_loss: 14.8151 - val_accuracy: 0.3152
Epoch 9428/10000
1/1 [==============================] - 0s 114ms/step - loss: 2.0201e-06 - accuracy: 1.0000 - val_loss: 14.8163 - val_accuracy: 0.3152
Epoch 9429/10000
1/1 [==============================] - 0s 105ms/step - loss: 2.0196e-06 - accuracy: 1.0000 - val_loss: 14.8175 - val_accuracy: 0.3152
Epoch 9430/10000
1/1 [==============================] - 0s 102ms/step - loss: 2.0192e-06 - accuracy: 1.0000 - val_loss: 14.8175 - val_accuracy: 0.3152
Epoch 9431/10000
1/1 [==============================] - 0s 100ms/step - loss: 2.0182e-06 - accuracy: 1.0000 - val_loss: 14.8175 - val_accuracy: 0.3152
Epoch 9432/10000
1/1 [==============================] - 0s 98ms/step - loss: 2.0142e-06 - accuracy: 1.0000 - val_loss: 14.8185 - val_accuracy: 0.3152
Epoch 9433/10000
1/1 [==============================] - 0s 104ms/step - loss: 2.0134e-06 - accuracy: 1.0000 - val_loss: 14.8199 - val_accuracy: 0.3152
Epoch 9434/10000
1/1 [==============================] - 0s 100ms/step - loss: 2.0127e-06 - accuracy: 1.0000 - val_loss: 14.8207 - val_accuracy: 0.3152
Epoch 9435/10000
1/1 [==============================] - 0s 102ms/step - loss: 2.0144e-06 - accuracy: 1.0000 - val_loss: 14.8203 - val_accuracy: 0.3152
Epoch 9436/10000
1/1 [==============================] - 0s 104ms/step - loss: 2.0106e-06 - accuracy: 1.0000 - val_loss: 14.8198 - val_accuracy: 0.3151
Epoch 9437/10000
1/1 [==============================] - 0s 104ms/step - loss: 2.0096e-06 - accuracy: 1.0000 - val_loss: 14.8204 - val_accuracy: 0.3152
Epoch 9438/10000
1/1 [==============================] - 0s 102ms/step - loss: 2.0065e-06 - accuracy: 1.0000 - val_loss: 14.8216 - val_accuracy: 0.3152
Epoch 9439/10000
1/1 [==============================] - 0s 103ms/step - loss: 2.0060e-06 - accuracy: 1.0000 - val_loss: 14.8220 - val_accuracy: 0.3152
Epoch 9440/10000
1/1 [==============================] - 0s 100ms/step - loss: 2.0041e-06 - accuracy: 1.0000 - val_loss: 14.8230 - val_accuracy: 0.3152
Epoch 9441/10000
1/1 [==============================] - 0s 102ms/step - loss: 2.0018e-06 - accuracy: 1.0000 - val_loss: 14.8248 - val_accuracy: 0.3152
Epoch 9442/10000
1/1 [==============================] - 0s 104ms/step - loss: 2.0008e-06 - accuracy: 1.0000 - val_loss: 14.8251 - val_accuracy: 0.3152
Epoch 9443/10000
1/1 [==============================] - 0s 103ms/step - loss: 2.0001e-06 - accuracy: 1.0000 - val_loss: 14.8243 - val_accuracy: 0.3152
Epoch 9444/10000
1/1 [==============================] - 0s 103ms/step - loss: 2.0020e-06 - accuracy: 1.0000 - val_loss: 14.8246 - val_accuracy: 0.3151
Epoch 9445/10000
1/1 [==============================] - 0s 107ms/step - loss: 2.0001e-06 - accuracy: 1.0000 - val_loss: 14.8258 - val_accuracy: 0.3152
Epoch 9446/10000
1/1 [==============================] - 0s 105ms/step - loss: 1.9984e-06 - accuracy: 1.0000 - val_loss: 14.8273 - val_accuracy: 0.3152
Epoch 9447/10000
1/1 [==============================] - 0s 107ms/step - loss: 1.9953e-06 - accuracy: 1.0000 - val_loss: 14.8278 - val_accuracy: 0.3152
Epoch 9448/10000
1/1 [==============================] - 0s 101ms/step - loss: 1.9944e-06 - accuracy: 1.0000 - val_loss: 14.8279 - val_accuracy: 0.3152
Epoch 9449/10000
1/1 [==============================] - 0s 104ms/step - loss: 1.9917e-06 - accuracy: 1.0000 - val_loss: 14.8284 - val_accuracy: 0.3152
Epoch 9450/10000
1/1 [==============================] - 0s 100ms/step - loss: 1.9917e-06 - accuracy: 1.0000 - val_loss: 14.8289 - val_accuracy: 0.3152
Epoch 9451/10000
1/1 [==============================] - 0s 100ms/step - loss: 1.9908e-06 - accuracy: 1.0000 - val_loss: 14.8291 - val_accuracy: 0.3152
Epoch 9452/10000
1/1 [==============================] - 0s 97ms/step - loss: 1.9903e-06 - accuracy: 1.0000 - val_loss: 14.8297 - val_accuracy: 0.3151
Epoch 9453/10000
1/1 [==============================] - 0s 105ms/step - loss: 1.9879e-06 - accuracy: 1.0000 - val_loss: 14.8312 - val_accuracy: 0.3151
Epoch 9454/10000
1/1 [==============================] - 0s 100ms/step - loss: 1.9841e-06 - accuracy: 1.0000 - val_loss: 14.8322 - val_accuracy: 0.3152
Epoch 9455/10000
1/1 [==============================] - 0s 102ms/step - loss: 1.9853e-06 - accuracy: 1.0000 - val_loss: 14.8320 - val_accuracy: 0.3152
Epoch 9456/10000
1/1 [==============================] - 0s 101ms/step - loss: 1.9848e-06 - accuracy: 1.0000 - val_loss: 14.8318 - val_accuracy: 0.3152
Epoch 9457/10000
1/1 [==============================] - 0s 103ms/step - loss: 1.9834e-06 - accuracy: 1.0000 - val_loss: 14.8323 - val_accuracy: 0.3152
Epoch 9458/10000
1/1 [==============================] - 0s 100ms/step - loss: 1.9803e-06 - accuracy: 1.0000 - val_loss: 14.8340 - val_accuracy: 0.3152
Epoch 9459/10000
1/1 [==============================] - 0s 99ms/step - loss: 1.9808e-06 - accuracy: 1.0000 - val_loss: 14.8354 - val_accuracy: 0.3151
Epoch 9460/10000
1/1 [==============================] - 0s 100ms/step - loss: 1.9813e-06 - accuracy: 1.0000 - val_loss: 14.8350 - val_accuracy: 0.3152
Epoch 9461/10000
1/1 [==============================] - 0s 106ms/step - loss: 1.9762e-06 - accuracy: 1.0000 - val_loss: 14.8344 - val_accuracy: 0.3152
Epoch 9462/10000
1/1 [==============================] - 0s 102ms/step - loss: 1.9755e-06 - accuracy: 1.0000 - val_loss: 14.8348 - val_accuracy: 0.3152
Epoch 9463/10000
1/1 [==============================] - 0s 106ms/step - loss: 1.9751e-06 - accuracy: 1.0000 - val_loss: 14.8356 - val_accuracy: 0.3152
Epoch 9464/10000
1/1 [==============================] - 0s 101ms/step - loss: 1.9748e-06 - accuracy: 1.0000 - val_loss: 14.8355 - val_accuracy: 0.3152
Epoch 9465/10000
1/1 [==============================] - 0s 102ms/step - loss: 1.9731e-06 - accuracy: 1.0000 - val_loss: 14.8361 - val_accuracy: 0.3152
Epoch 9466/10000
1/1 [==============================] - 0s 104ms/step - loss: 1.9724e-06 - accuracy: 1.0000 - val_loss: 14.8377 - val_accuracy: 0.3152
Epoch 9467/10000
1/1 [==============================] - 0s 107ms/step - loss: 1.9708e-06 - accuracy: 1.0000 - val_loss: 14.8397 - val_accuracy: 0.3152
Epoch 9468/10000
1/1 [==============================] - 0s 104ms/step - loss: 1.9698e-06 - accuracy: 1.0000 - val_loss: 14.8400 - val_accuracy: 0.3152
Epoch 9469/10000
1/1 [==============================] - 0s 104ms/step - loss: 1.9689e-06 - accuracy: 1.0000 - val_loss: 14.8394 - val_accuracy: 0.3151
Epoch 9470/10000
1/1 [==============================] - 0s 102ms/step - loss: 1.9684e-06 - accuracy: 1.0000 - val_loss: 14.8395 - val_accuracy: 0.3151
Epoch 9471/10000
1/1 [==============================] - 0s 101ms/step - loss: 1.9679e-06 - accuracy: 1.0000 - val_loss: 14.8405 - val_accuracy: 0.3152
Epoch 9472/10000
1/1 [==============================] - 0s 105ms/step - loss: 1.9662e-06 - accuracy: 1.0000 - val_loss: 14.8416 - val_accuracy: 0.3152
Epoch 9473/10000
1/1 [==============================] - 0s 108ms/step - loss: 1.9641e-06 - accuracy: 1.0000 - val_loss: 14.8424 - val_accuracy: 0.3152
Epoch 9474/10000
1/1 [==============================] - 0s 104ms/step - loss: 1.9643e-06 - accuracy: 1.0000 - val_loss: 14.8430 - val_accuracy: 0.3152
Epoch 9475/10000
1/1 [==============================] - 0s 100ms/step - loss: 1.9631e-06 - accuracy: 1.0000 - val_loss: 14.8437 - val_accuracy: 0.3151
Epoch 9476/10000
1/1 [==============================] - 0s 106ms/step - loss: 1.9629e-06 - accuracy: 1.0000 - val_loss: 14.8441 - val_accuracy: 0.3152
Epoch 9477/10000
1/1 [==============================] - 0s 108ms/step - loss: 1.9607e-06 - accuracy: 1.0000 - val_loss: 14.8444 - val_accuracy: 0.3152
Epoch 9478/10000
1/1 [==============================] - 0s 102ms/step - loss: 1.9579e-06 - accuracy: 1.0000 - val_loss: 14.8447 - val_accuracy: 0.3152
Epoch 9479/10000
1/1 [==============================] - 0s 101ms/step - loss: 1.9581e-06 - accuracy: 1.0000 - val_loss: 14.8458 - val_accuracy: 0.3152
Epoch 9480/10000
1/1 [==============================] - 0s 105ms/step - loss: 1.9567e-06 - accuracy: 1.0000 - val_loss: 14.8472 - val_accuracy: 0.3152
Epoch 9481/10000
1/1 [==============================] - 0s 111ms/step - loss: 1.9555e-06 - accuracy: 1.0000 - val_loss: 14.8474 - val_accuracy: 0.3152
Epoch 9482/10000
1/1 [==============================] - 0s 105ms/step - loss: 1.9536e-06 - accuracy: 1.0000 - val_loss: 14.8472 - val_accuracy: 0.3152
Epoch 9483/10000
1/1 [==============================] - 0s 107ms/step - loss: 1.9519e-06 - accuracy: 1.0000 - val_loss: 14.8477 - val_accuracy: 0.3152
Epoch 9484/10000
1/1 [==============================] - 0s 112ms/step - loss: 1.9536e-06 - accuracy: 1.0000 - val_loss: 14.8486 - val_accuracy: 0.3152
Epoch 9485/10000
1/1 [==============================] - 0s 106ms/step - loss: 1.9519e-06 - accuracy: 1.0000 - val_loss: 14.8495 - val_accuracy: 0.3152
Epoch 9486/10000
1/1 [==============================] - 0s 106ms/step - loss: 1.9507e-06 - accuracy: 1.0000 - val_loss: 14.8500 - val_accuracy: 0.3152
Epoch 9487/10000
1/1 [==============================] - 0s 102ms/step - loss: 1.9503e-06 - accuracy: 1.0000 - val_loss: 14.8507 - val_accuracy: 0.3151
Epoch 9488/10000
1/1 [==============================] - 0s 102ms/step - loss: 1.9476e-06 - accuracy: 1.0000 - val_loss: 14.8514 - val_accuracy: 0.3151
Epoch 9489/10000
1/1 [==============================] - 0s 103ms/step - loss: 1.9467e-06 - accuracy: 1.0000 - val_loss: 14.8517 - val_accuracy: 0.3151
Epoch 9490/10000
1/1 [==============================] - 0s 103ms/step - loss: 1.9450e-06 - accuracy: 1.0000 - val_loss: 14.8518 - val_accuracy: 0.3151
Epoch 9491/10000
1/1 [==============================] - 0s 110ms/step - loss: 1.9433e-06 - accuracy: 1.0000 - val_loss: 14.8522 - val_accuracy: 0.3151
Epoch 9492/10000
1/1 [==============================] - 0s 110ms/step - loss: 1.9438e-06 - accuracy: 1.0000 - val_loss: 14.8532 - val_accuracy: 0.3151
Epoch 9493/10000
1/1 [==============================] - 0s 108ms/step - loss: 1.9414e-06 - accuracy: 1.0000 - val_loss: 14.8540 - val_accuracy: 0.3151
Epoch 9494/10000
1/1 [==============================] - 0s 105ms/step - loss: 1.9400e-06 - accuracy: 1.0000 - val_loss: 14.8544 - val_accuracy: 0.3152
Epoch 9495/10000
1/1 [==============================] - 0s 104ms/step - loss: 1.9383e-06 - accuracy: 1.0000 - val_loss: 14.8547 - val_accuracy: 0.3151
Epoch 9496/10000
1/1 [==============================] - 0s 105ms/step - loss: 1.9371e-06 - accuracy: 1.0000 - val_loss: 14.8549 - val_accuracy: 0.3151
Epoch 9497/10000
1/1 [==============================] - 0s 108ms/step - loss: 1.9355e-06 - accuracy: 1.0000 - val_loss: 14.8555 - val_accuracy: 0.3151
Epoch 9498/10000
1/1 [==============================] - 0s 111ms/step - loss: 1.9345e-06 - accuracy: 1.0000 - val_loss: 14.8564 - val_accuracy: 0.3152
Epoch 9499/10000
1/1 [==============================] - 0s 106ms/step - loss: 1.9355e-06 - accuracy: 1.0000 - val_loss: 14.8570 - val_accuracy: 0.3151
Epoch 9500/10000
1/1 [==============================] - 0s 107ms/step - loss: 1.9348e-06 - accuracy: 1.0000 - val_loss: 14.8577 - val_accuracy: 0.3151
Epoch 9501/10000
1/1 [==============================] - 0s 101ms/step - loss: 1.9312e-06 - accuracy: 1.0000 - val_loss: 14.8583 - val_accuracy: 0.3151
Epoch 9502/10000
1/1 [==============================] - 0s 107ms/step - loss: 1.9319e-06 - accuracy: 1.0000 - val_loss: 14.8584 - val_accuracy: 0.3151
Epoch 9503/10000
1/1 [==============================] - 0s 102ms/step - loss: 1.9312e-06 - accuracy: 1.0000 - val_loss: 14.8588 - val_accuracy: 0.3151
Epoch 9504/10000
1/1 [==============================] - 0s 104ms/step - loss: 1.9286e-06 - accuracy: 1.0000 - val_loss: 14.8597 - val_accuracy: 0.3151
Epoch 9505/10000
1/1 [==============================] - 0s 102ms/step - loss: 1.9283e-06 - accuracy: 1.0000 - val_loss: 14.8604 - val_accuracy: 0.3151
Epoch 9506/10000
1/1 [==============================] - 0s 107ms/step - loss: 1.9257e-06 - accuracy: 1.0000 - val_loss: 14.8615 - val_accuracy: 0.3152
Epoch 9507/10000
1/1 [==============================] - 0s 108ms/step - loss: 1.9262e-06 - accuracy: 1.0000 - val_loss: 14.8621 - val_accuracy: 0.3152
Epoch 9508/10000
1/1 [==============================] - 0s 101ms/step - loss: 1.9267e-06 - accuracy: 1.0000 - val_loss: 14.8621 - val_accuracy: 0.3151
Epoch 9509/10000
1/1 [==============================] - 0s 111ms/step - loss: 1.9240e-06 - accuracy: 1.0000 - val_loss: 14.8621 - val_accuracy: 0.3151
Epoch 9510/10000
1/1 [==============================] - 0s 106ms/step - loss: 1.9238e-06 - accuracy: 1.0000 - val_loss: 14.8629 - val_accuracy: 0.3151
Epoch 9511/10000
1/1 [==============================] - 0s 102ms/step - loss: 1.9209e-06 - accuracy: 1.0000 - val_loss: 14.8644 - val_accuracy: 0.3151
Epoch 9512/10000
1/1 [==============================] - 0s 100ms/step - loss: 1.9221e-06 - accuracy: 1.0000 - val_loss: 14.8651 - val_accuracy: 0.3152
Epoch 9513/10000
1/1 [==============================] - 0s 105ms/step - loss: 1.9224e-06 - accuracy: 1.0000 - val_loss: 14.8652 - val_accuracy: 0.3152
Epoch 9514/10000
1/1 [==============================] - 0s 104ms/step - loss: 1.9197e-06 - accuracy: 1.0000 - val_loss: 14.8656 - val_accuracy: 0.3151
Epoch 9515/10000
1/1 [==============================] - 0s 105ms/step - loss: 1.9190e-06 - accuracy: 1.0000 - val_loss: 14.8665 - val_accuracy: 0.3151
Epoch 9516/10000
1/1 [==============================] - 0s 108ms/step - loss: 1.9171e-06 - accuracy: 1.0000 - val_loss: 14.8675 - val_accuracy: 0.3151
Epoch 9517/10000
1/1 [==============================] - 0s 104ms/step - loss: 1.9176e-06 - accuracy: 1.0000 - val_loss: 14.8680 - val_accuracy: 0.3151
Epoch 9518/10000
1/1 [==============================] - 0s 99ms/step - loss: 1.9164e-06 - accuracy: 1.0000 - val_loss: 14.8676 - val_accuracy: 0.3151
Epoch 9519/10000
1/1 [==============================] - 0s 102ms/step - loss: 1.9157e-06 - accuracy: 1.0000 - val_loss: 14.8678 - val_accuracy: 0.3152
Epoch 9520/10000
1/1 [==============================] - 0s 106ms/step - loss: 1.9143e-06 - accuracy: 1.0000 - val_loss: 14.8684 - val_accuracy: 0.3152
Epoch 9521/10000
1/1 [==============================] - 0s 107ms/step - loss: 1.9145e-06 - accuracy: 1.0000 - val_loss: 14.8694 - val_accuracy: 0.3151
Epoch 9522/10000
1/1 [==============================] - 0s 105ms/step - loss: 1.9124e-06 - accuracy: 1.0000 - val_loss: 14.8704 - val_accuracy: 0.3151
Epoch 9523/10000
1/1 [==============================] - 0s 101ms/step - loss: 1.9097e-06 - accuracy: 1.0000 - val_loss: 14.8713 - val_accuracy: 0.3151
Epoch 9524/10000
1/1 [==============================] - 0s 102ms/step - loss: 1.9102e-06 - accuracy: 1.0000 - val_loss: 14.8717 - val_accuracy: 0.3151
Epoch 9525/10000
1/1 [==============================] - 0s 105ms/step - loss: 1.9097e-06 - accuracy: 1.0000 - val_loss: 14.8720 - val_accuracy: 0.3151
Epoch 9526/10000
1/1 [==============================] - 0s 98ms/step - loss: 1.9083e-06 - accuracy: 1.0000 - val_loss: 14.8724 - val_accuracy: 0.3151
Epoch 9527/10000
1/1 [==============================] - 0s 102ms/step - loss: 1.9071e-06 - accuracy: 1.0000 - val_loss: 14.8732 - val_accuracy: 0.3151
Epoch 9528/10000
1/1 [==============================] - 0s 103ms/step - loss: 1.9047e-06 - accuracy: 1.0000 - val_loss: 14.8742 - val_accuracy: 0.3151
Epoch 9529/10000
1/1 [==============================] - 0s 101ms/step - loss: 1.9047e-06 - accuracy: 1.0000 - val_loss: 14.8744 - val_accuracy: 0.3151
Epoch 9530/10000
1/1 [==============================] - 0s 111ms/step - loss: 1.9028e-06 - accuracy: 1.0000 - val_loss: 14.8747 - val_accuracy: 0.3151
Epoch 9531/10000
1/1 [==============================] - 0s 104ms/step - loss: 1.8995e-06 - accuracy: 1.0000 - val_loss: 14.8753 - val_accuracy: 0.3151
Epoch 9532/10000
1/1 [==============================] - 0s 108ms/step - loss: 1.9007e-06 - accuracy: 1.0000 - val_loss: 14.8766 - val_accuracy: 0.3152
Epoch 9533/10000
1/1 [==============================] - 0s 98ms/step - loss: 1.8995e-06 - accuracy: 1.0000 - val_loss: 14.8772 - val_accuracy: 0.3151
Epoch 9534/10000
1/1 [==============================] - 0s 103ms/step - loss: 1.8983e-06 - accuracy: 1.0000 - val_loss: 14.8771 - val_accuracy: 0.3151
Epoch 9535/10000
1/1 [==============================] - 0s 102ms/step - loss: 1.8969e-06 - accuracy: 1.0000 - val_loss: 14.8771 - val_accuracy: 0.3151
Epoch 9536/10000
1/1 [==============================] - 0s 105ms/step - loss: 1.8966e-06 - accuracy: 1.0000 - val_loss: 14.8777 - val_accuracy: 0.3151
Epoch 9537/10000
1/1 [==============================] - 0s 102ms/step - loss: 1.8940e-06 - accuracy: 1.0000 - val_loss: 14.8792 - val_accuracy: 0.3151
Epoch 9538/10000
1/1 [==============================] - 0s 102ms/step - loss: 1.8947e-06 - accuracy: 1.0000 - val_loss: 14.8800 - val_accuracy: 0.3151
Epoch 9539/10000
1/1 [==============================] - 0s 101ms/step - loss: 1.8935e-06 - accuracy: 1.0000 - val_loss: 14.8801 - val_accuracy: 0.3151
Epoch 9540/10000
1/1 [==============================] - 0s 102ms/step - loss: 1.8923e-06 - accuracy: 1.0000 - val_loss: 14.8804 - val_accuracy: 0.3151
Epoch 9541/10000
1/1 [==============================] - 0s 103ms/step - loss: 1.8918e-06 - accuracy: 1.0000 - val_loss: 14.8812 - val_accuracy: 0.3151
Epoch 9542/10000
1/1 [==============================] - 0s 101ms/step - loss: 1.8892e-06 - accuracy: 1.0000 - val_loss: 14.8825 - val_accuracy: 0.3151
Epoch 9543/10000
1/1 [==============================] - 0s 101ms/step - loss: 1.8892e-06 - accuracy: 1.0000 - val_loss: 14.8827 - val_accuracy: 0.3151
Epoch 9544/10000
1/1 [==============================] - 0s 107ms/step - loss: 1.8866e-06 - accuracy: 1.0000 - val_loss: 14.8822 - val_accuracy: 0.3151
Epoch 9545/10000
1/1 [==============================] - 0s 98ms/step - loss: 1.8856e-06 - accuracy: 1.0000 - val_loss: 14.8827 - val_accuracy: 0.3151
Epoch 9546/10000
1/1 [==============================] - 0s 103ms/step - loss: 1.8849e-06 - accuracy: 1.0000 - val_loss: 14.8837 - val_accuracy: 0.3151
Epoch 9547/10000
1/1 [==============================] - 0s 105ms/step - loss: 1.8852e-06 - accuracy: 1.0000 - val_loss: 14.8843 - val_accuracy: 0.3151
Epoch 9548/10000
1/1 [==============================] - 0s 102ms/step - loss: 1.8835e-06 - accuracy: 1.0000 - val_loss: 14.8848 - val_accuracy: 0.3152
Epoch 9549/10000
1/1 [==============================] - 0s 106ms/step - loss: 1.8821e-06 - accuracy: 1.0000 - val_loss: 14.8861 - val_accuracy: 0.3152
Epoch 9550/10000
1/1 [==============================] - 0s 105ms/step - loss: 1.8804e-06 - accuracy: 1.0000 - val_loss: 14.8869 - val_accuracy: 0.3151
Epoch 9551/10000
1/1 [==============================] - 0s 101ms/step - loss: 1.8806e-06 - accuracy: 1.0000 - val_loss: 14.8870 - val_accuracy: 0.3151
Epoch 9552/10000
1/1 [==============================] - 0s 104ms/step - loss: 1.8785e-06 - accuracy: 1.0000 - val_loss: 14.8865 - val_accuracy: 0.3151
Epoch 9553/10000
1/1 [==============================] - 0s 100ms/step - loss: 1.8775e-06 - accuracy: 1.0000 - val_loss: 14.8869 - val_accuracy: 0.3151
Epoch 9554/10000
1/1 [==============================] - 0s 99ms/step - loss: 1.8761e-06 - accuracy: 1.0000 - val_loss: 14.8882 - val_accuracy: 0.3151
Epoch 9555/10000
1/1 [==============================] - 0s 104ms/step - loss: 1.8744e-06 - accuracy: 1.0000 - val_loss: 14.8896 - val_accuracy: 0.3152
Epoch 9556/10000
1/1 [==============================] - 0s 99ms/step - loss: 1.8732e-06 - accuracy: 1.0000 - val_loss: 14.8897 - val_accuracy: 0.3151
Epoch 9557/10000
1/1 [==============================] - 0s 106ms/step - loss: 1.8711e-06 - accuracy: 1.0000 - val_loss: 14.8896 - val_accuracy: 0.3151
Epoch 9558/10000
1/1 [==============================] - 0s 110ms/step - loss: 1.8721e-06 - accuracy: 1.0000 - val_loss: 14.8898 - val_accuracy: 0.3151
Epoch 9559/10000
1/1 [==============================] - 0s 103ms/step - loss: 1.8692e-06 - accuracy: 1.0000 - val_loss: 14.8908 - val_accuracy: 0.3151
Epoch 9560/10000
1/1 [==============================] - 0s 103ms/step - loss: 1.8685e-06 - accuracy: 1.0000 - val_loss: 14.8924 - val_accuracy: 0.3152
Epoch 9561/10000
1/1 [==============================] - 0s 101ms/step - loss: 1.8687e-06 - accuracy: 1.0000 - val_loss: 14.8933 - val_accuracy: 0.3152
Epoch 9562/10000
1/1 [==============================] - 0s 99ms/step - loss: 1.8682e-06 - accuracy: 1.0000 - val_loss: 14.8933 - val_accuracy: 0.3152
Epoch 9563/10000
1/1 [==============================] - 0s 99ms/step - loss: 1.8671e-06 - accuracy: 1.0000 - val_loss: 14.8931 - val_accuracy: 0.3151
Epoch 9564/10000
1/1 [==============================] - 0s 104ms/step - loss: 1.8654e-06 - accuracy: 1.0000 - val_loss: 14.8936 - val_accuracy: 0.3151
Epoch 9565/10000
1/1 [==============================] - 0s 104ms/step - loss: 1.8640e-06 - accuracy: 1.0000 - val_loss: 14.8945 - val_accuracy: 0.3151
Epoch 9566/10000
1/1 [==============================] - 0s 105ms/step - loss: 1.8644e-06 - accuracy: 1.0000 - val_loss: 14.8949 - val_accuracy: 0.3151
Epoch 9567/10000
1/1 [==============================] - 0s 106ms/step - loss: 1.8628e-06 - accuracy: 1.0000 - val_loss: 14.8957 - val_accuracy: 0.3152
Epoch 9568/10000
1/1 [==============================] - 0s 108ms/step - loss: 1.8616e-06 - accuracy: 1.0000 - val_loss: 14.8972 - val_accuracy: 0.3151
Epoch 9569/10000
1/1 [==============================] - 0s 102ms/step - loss: 1.8601e-06 - accuracy: 1.0000 - val_loss: 14.8977 - val_accuracy: 0.3151
Epoch 9570/10000
1/1 [==============================] - 0s 109ms/step - loss: 1.8587e-06 - accuracy: 1.0000 - val_loss: 14.8975 - val_accuracy: 0.3151
Epoch 9571/10000
1/1 [==============================] - 0s 104ms/step - loss: 1.8578e-06 - accuracy: 1.0000 - val_loss: 14.8976 - val_accuracy: 0.3151
Epoch 9572/10000
1/1 [==============================] - 0s 108ms/step - loss: 1.8561e-06 - accuracy: 1.0000 - val_loss: 14.8985 - val_accuracy: 0.3151
Epoch 9573/10000
1/1 [==============================] - 0s 100ms/step - loss: 1.8547e-06 - accuracy: 1.0000 - val_loss: 14.9000 - val_accuracy: 0.3151
Epoch 9574/10000
1/1 [==============================] - 0s 104ms/step - loss: 1.8544e-06 - accuracy: 1.0000 - val_loss: 14.9006 - val_accuracy: 0.3152
Epoch 9575/10000
1/1 [==============================] - 0s 100ms/step - loss: 1.8527e-06 - accuracy: 1.0000 - val_loss: 14.9000 - val_accuracy: 0.3151
Epoch 9576/10000
1/1 [==============================] - 0s 103ms/step - loss: 1.8525e-06 - accuracy: 1.0000 - val_loss: 14.9001 - val_accuracy: 0.3151
Epoch 9577/10000
1/1 [==============================] - 0s 101ms/step - loss: 1.8506e-06 - accuracy: 1.0000 - val_loss: 14.9015 - val_accuracy: 0.3151
Epoch 9578/10000
1/1 [==============================] - 0s 106ms/step - loss: 1.8496e-06 - accuracy: 1.0000 - val_loss: 14.9027 - val_accuracy: 0.3151
Epoch 9579/10000
1/1 [==============================] - 0s 106ms/step - loss: 1.8504e-06 - accuracy: 1.0000 - val_loss: 14.9031 - val_accuracy: 0.3152
Epoch 9580/10000
1/1 [==============================] - 0s 104ms/step - loss: 1.8487e-06 - accuracy: 1.0000 - val_loss: 14.9033 - val_accuracy: 0.3151
Epoch 9581/10000
1/1 [==============================] - 0s 104ms/step - loss: 1.8480e-06 - accuracy: 1.0000 - val_loss: 14.9040 - val_accuracy: 0.3151
Epoch 9582/10000
1/1 [==============================] - 0s 103ms/step - loss: 1.8461e-06 - accuracy: 1.0000 - val_loss: 14.9047 - val_accuracy: 0.3151
Epoch 9583/10000
1/1 [==============================] - 0s 106ms/step - loss: 1.8444e-06 - accuracy: 1.0000 - val_loss: 14.9050 - val_accuracy: 0.3152
Epoch 9584/10000
1/1 [==============================] - 0s 102ms/step - loss: 1.8430e-06 - accuracy: 1.0000 - val_loss: 14.9055 - val_accuracy: 0.3152
Epoch 9585/10000
1/1 [==============================] - 0s 106ms/step - loss: 1.8432e-06 - accuracy: 1.0000 - val_loss: 14.9059 - val_accuracy: 0.3151
Epoch 9586/10000
1/1 [==============================] - 0s 101ms/step - loss: 1.8430e-06 - accuracy: 1.0000 - val_loss: 14.9064 - val_accuracy: 0.3151
Epoch 9587/10000
1/1 [==============================] - 0s 105ms/step - loss: 1.8420e-06 - accuracy: 1.0000 - val_loss: 14.9069 - val_accuracy: 0.3151
Epoch 9588/10000
1/1 [==============================] - 0s 99ms/step - loss: 1.8382e-06 - accuracy: 1.0000 - val_loss: 14.9074 - val_accuracy: 0.3151
Epoch 9589/10000
1/1 [==============================] - 0s 103ms/step - loss: 1.8377e-06 - accuracy: 1.0000 - val_loss: 14.9086 - val_accuracy: 0.3151
Epoch 9590/10000
1/1 [==============================] - 0s 99ms/step - loss: 1.8365e-06 - accuracy: 1.0000 - val_loss: 14.9102 - val_accuracy: 0.3152
Epoch 9591/10000
1/1 [==============================] - 0s 103ms/step - loss: 1.8363e-06 - accuracy: 1.0000 - val_loss: 14.9100 - val_accuracy: 0.3152
Epoch 9592/10000
1/1 [==============================] - 0s 104ms/step - loss: 1.8349e-06 - accuracy: 1.0000 - val_loss: 14.9099 - val_accuracy: 0.3151
Epoch 9593/10000
1/1 [==============================] - 0s 116ms/step - loss: 1.8325e-06 - accuracy: 1.0000 - val_loss: 14.9105 - val_accuracy: 0.3151
Epoch 9594/10000
1/1 [==============================] - 0s 106ms/step - loss: 1.8330e-06 - accuracy: 1.0000 - val_loss: 14.9116 - val_accuracy: 0.3151
Epoch 9595/10000
1/1 [==============================] - 0s 109ms/step - loss: 1.8318e-06 - accuracy: 1.0000 - val_loss: 14.9125 - val_accuracy: 0.3152
Epoch 9596/10000
1/1 [==============================] - 0s 99ms/step - loss: 1.8306e-06 - accuracy: 1.0000 - val_loss: 14.9130 - val_accuracy: 0.3152
Epoch 9597/10000
1/1 [==============================] - 0s 105ms/step - loss: 1.8287e-06 - accuracy: 1.0000 - val_loss: 14.9129 - val_accuracy: 0.3152
Epoch 9598/10000
1/1 [==============================] - 0s 105ms/step - loss: 1.8270e-06 - accuracy: 1.0000 - val_loss: 14.9133 - val_accuracy: 0.3151
Epoch 9599/10000
1/1 [==============================] - 0s 108ms/step - loss: 1.8270e-06 - accuracy: 1.0000 - val_loss: 14.9143 - val_accuracy: 0.3151
Epoch 9600/10000
1/1 [==============================] - 0s 112ms/step - loss: 1.8251e-06 - accuracy: 1.0000 - val_loss: 14.9148 - val_accuracy: 0.3152
Epoch 9601/10000
1/1 [==============================] - 0s 109ms/step - loss: 1.8246e-06 - accuracy: 1.0000 - val_loss: 14.9155 - val_accuracy: 0.3152
Epoch 9602/10000
1/1 [==============================] - 0s 105ms/step - loss: 1.8234e-06 - accuracy: 1.0000 - val_loss: 14.9163 - val_accuracy: 0.3151
Epoch 9603/10000
1/1 [==============================] - 0s 117ms/step - loss: 1.8208e-06 - accuracy: 1.0000 - val_loss: 14.9169 - val_accuracy: 0.3151
Epoch 9604/10000
1/1 [==============================] - 0s 107ms/step - loss: 1.8208e-06 - accuracy: 1.0000 - val_loss: 14.9167 - val_accuracy: 0.3152
Epoch 9605/10000
1/1 [==============================] - 0s 111ms/step - loss: 1.8229e-06 - accuracy: 1.0000 - val_loss: 14.9175 - val_accuracy: 0.3152
Epoch 9606/10000
1/1 [==============================] - 0s 107ms/step - loss: 1.8201e-06 - accuracy: 1.0000 - val_loss: 14.9185 - val_accuracy: 0.3152
Epoch 9607/10000
1/1 [==============================] - 0s 110ms/step - loss: 1.8201e-06 - accuracy: 1.0000 - val_loss: 14.9191 - val_accuracy: 0.3151
Epoch 9608/10000
1/1 [==============================] - 0s 102ms/step - loss: 1.8153e-06 - accuracy: 1.0000 - val_loss: 14.9192 - val_accuracy: 0.3151
Epoch 9609/10000
1/1 [==============================] - 0s 109ms/step - loss: 1.8158e-06 - accuracy: 1.0000 - val_loss: 14.9186 - val_accuracy: 0.3151
Epoch 9610/10000
1/1 [==============================] - 0s 105ms/step - loss: 1.8158e-06 - accuracy: 1.0000 - val_loss: 14.9189 - val_accuracy: 0.3151
Epoch 9611/10000
1/1 [==============================] - 0s 101ms/step - loss: 1.8156e-06 - accuracy: 1.0000 - val_loss: 14.9204 - val_accuracy: 0.3152
Epoch 9612/10000
1/1 [==============================] - 0s 103ms/step - loss: 1.8139e-06 - accuracy: 1.0000 - val_loss: 14.9224 - val_accuracy: 0.3152
Epoch 9613/10000
1/1 [==============================] - 0s 108ms/step - loss: 1.8113e-06 - accuracy: 1.0000 - val_loss: 14.9232 - val_accuracy: 0.3151
Epoch 9614/10000
1/1 [==============================] - 0s 109ms/step - loss: 1.8103e-06 - accuracy: 1.0000 - val_loss: 14.9227 - val_accuracy: 0.3151
Epoch 9615/10000
1/1 [==============================] - 0s 105ms/step - loss: 1.8103e-06 - accuracy: 1.0000 - val_loss: 14.9223 - val_accuracy: 0.3152
Epoch 9616/10000
1/1 [==============================] - 0s 104ms/step - loss: 1.8082e-06 - accuracy: 1.0000 - val_loss: 14.9231 - val_accuracy: 0.3152
Epoch 9617/10000
1/1 [==============================] - 0s 98ms/step - loss: 1.8082e-06 - accuracy: 1.0000 - val_loss: 14.9246 - val_accuracy: 0.3152
Epoch 9618/10000
1/1 [==============================] - 0s 99ms/step - loss: 1.8077e-06 - accuracy: 1.0000 - val_loss: 14.9257 - val_accuracy: 0.3151
Epoch 9619/10000
1/1 [==============================] - 0s 104ms/step - loss: 1.8053e-06 - accuracy: 1.0000 - val_loss: 14.9264 - val_accuracy: 0.3151
Epoch 9620/10000
1/1 [==============================] - 0s 102ms/step - loss: 1.8022e-06 - accuracy: 1.0000 - val_loss: 14.9265 - val_accuracy: 0.3152
Epoch 9621/10000
1/1 [==============================] - 0s 101ms/step - loss: 1.8017e-06 - accuracy: 1.0000 - val_loss: 14.9266 - val_accuracy: 0.3152
Epoch 9622/10000
1/1 [==============================] - 0s 99ms/step - loss: 1.8001e-06 - accuracy: 1.0000 - val_loss: 14.9267 - val_accuracy: 0.3152
Epoch 9623/10000
1/1 [==============================] - 0s 101ms/step - loss: 1.8012e-06 - accuracy: 1.0000 - val_loss: 14.9272 - val_accuracy: 0.3152
Epoch 9624/10000
1/1 [==============================] - 0s 101ms/step - loss: 1.7984e-06 - accuracy: 1.0000 - val_loss: 14.9285 - val_accuracy: 0.3151
Epoch 9625/10000
1/1 [==============================] - 0s 100ms/step - loss: 1.7965e-06 - accuracy: 1.0000 - val_loss: 14.9298 - val_accuracy: 0.3152
Epoch 9626/10000
1/1 [==============================] - 0s 101ms/step - loss: 1.7955e-06 - accuracy: 1.0000 - val_loss: 14.9304 - val_accuracy: 0.3152
Epoch 9627/10000
1/1 [==============================] - 0s 101ms/step - loss: 1.7965e-06 - accuracy: 1.0000 - val_loss: 14.9300 - val_accuracy: 0.3151
Epoch 9628/10000
1/1 [==============================] - 0s 101ms/step - loss: 1.7943e-06 - accuracy: 1.0000 - val_loss: 14.9301 - val_accuracy: 0.3151
Epoch 9629/10000
1/1 [==============================] - 0s 104ms/step - loss: 1.7941e-06 - accuracy: 1.0000 - val_loss: 14.9307 - val_accuracy: 0.3151
Epoch 9630/10000
1/1 [==============================] - 0s 104ms/step - loss: 1.7912e-06 - accuracy: 1.0000 - val_loss: 14.9317 - val_accuracy: 0.3151
Epoch 9631/10000
1/1 [==============================] - 0s 102ms/step - loss: 1.7891e-06 - accuracy: 1.0000 - val_loss: 14.9327 - val_accuracy: 0.3152
Epoch 9632/10000
1/1 [==============================] - 0s 101ms/step - loss: 1.7900e-06 - accuracy: 1.0000 - val_loss: 14.9336 - val_accuracy: 0.3152
Epoch 9633/10000
1/1 [==============================] - 0s 102ms/step - loss: 1.7898e-06 - accuracy: 1.0000 - val_loss: 14.9335 - val_accuracy: 0.3152
Epoch 9634/10000
1/1 [==============================] - 0s 101ms/step - loss: 1.7879e-06 - accuracy: 1.0000 - val_loss: 14.9341 - val_accuracy: 0.3151
Epoch 9635/10000
1/1 [==============================] - 0s 101ms/step - loss: 1.7879e-06 - accuracy: 1.0000 - val_loss: 14.9344 - val_accuracy: 0.3151
Epoch 9636/10000
1/1 [==============================] - 0s 99ms/step - loss: 1.7848e-06 - accuracy: 1.0000 - val_loss: 14.9347 - val_accuracy: 0.3151
Epoch 9637/10000
1/1 [==============================] - 0s 100ms/step - loss: 1.7841e-06 - accuracy: 1.0000 - val_loss: 14.9355 - val_accuracy: 0.3152
Epoch 9638/10000
1/1 [==============================] - 0s 110ms/step - loss: 1.7831e-06 - accuracy: 1.0000 - val_loss: 14.9369 - val_accuracy: 0.3152
Epoch 9639/10000
1/1 [==============================] - 0s 99ms/step - loss: 1.7829e-06 - accuracy: 1.0000 - val_loss: 14.9375 - val_accuracy: 0.3152
Epoch 9640/10000
1/1 [==============================] - 0s 103ms/step - loss: 1.7807e-06 - accuracy: 1.0000 - val_loss: 14.9375 - val_accuracy: 0.3152
Epoch 9641/10000
1/1 [==============================] - 0s 99ms/step - loss: 1.7817e-06 - accuracy: 1.0000 - val_loss: 14.9374 - val_accuracy: 0.3151
Epoch 9642/10000
1/1 [==============================] - 0s 100ms/step - loss: 1.7796e-06 - accuracy: 1.0000 - val_loss: 14.9382 - val_accuracy: 0.3152
Epoch 9643/10000
1/1 [==============================] - 0s 105ms/step - loss: 1.7786e-06 - accuracy: 1.0000 - val_loss: 14.9394 - val_accuracy: 0.3152
Epoch 9644/10000
1/1 [==============================] - 0s 99ms/step - loss: 1.7781e-06 - accuracy: 1.0000 - val_loss: 14.9400 - val_accuracy: 0.3150
Epoch 9645/10000
1/1 [==============================] - 0s 98ms/step - loss: 1.7767e-06 - accuracy: 1.0000 - val_loss: 14.9403 - val_accuracy: 0.3150
Epoch 9646/10000
1/1 [==============================] - 0s 103ms/step - loss: 1.7762e-06 - accuracy: 1.0000 - val_loss: 14.9404 - val_accuracy: 0.3152
Epoch 9647/10000
1/1 [==============================] - 0s 106ms/step - loss: 1.7769e-06 - accuracy: 1.0000 - val_loss: 14.9412 - val_accuracy: 0.3152
Epoch 9648/10000
1/1 [==============================] - 0s 106ms/step - loss: 1.7729e-06 - accuracy: 1.0000 - val_loss: 14.9425 - val_accuracy: 0.3152
Epoch 9649/10000
1/1 [==============================] - 0s 101ms/step - loss: 1.7722e-06 - accuracy: 1.0000 - val_loss: 14.9435 - val_accuracy: 0.3152
Epoch 9650/10000
1/1 [==============================] - 0s 103ms/step - loss: 1.7710e-06 - accuracy: 1.0000 - val_loss: 14.9438 - val_accuracy: 0.3152
Epoch 9651/10000
1/1 [==============================] - 0s 102ms/step - loss: 1.7724e-06 - accuracy: 1.0000 - val_loss: 14.9436 - val_accuracy: 0.3152
Epoch 9652/10000
1/1 [==============================] - 0s 107ms/step - loss: 1.7705e-06 - accuracy: 1.0000 - val_loss: 14.9438 - val_accuracy: 0.3152
Epoch 9653/10000
1/1 [==============================] - 0s 103ms/step - loss: 1.7688e-06 - accuracy: 1.0000 - val_loss: 14.9451 - val_accuracy: 0.3151
Epoch 9654/10000
1/1 [==============================] - 0s 101ms/step - loss: 1.7679e-06 - accuracy: 1.0000 - val_loss: 14.9462 - val_accuracy: 0.3151
Epoch 9655/10000
1/1 [==============================] - 0s 104ms/step - loss: 1.7664e-06 - accuracy: 1.0000 - val_loss: 14.9463 - val_accuracy: 0.3150
Epoch 9656/10000
1/1 [==============================] - 0s 106ms/step - loss: 1.7652e-06 - accuracy: 1.0000 - val_loss: 14.9464 - val_accuracy: 0.3152
Epoch 9657/10000
1/1 [==============================] - 0s 103ms/step - loss: 1.7648e-06 - accuracy: 1.0000 - val_loss: 14.9471 - val_accuracy: 0.3152
Epoch 9658/10000
1/1 [==============================] - 0s 101ms/step - loss: 1.7621e-06 - accuracy: 1.0000 - val_loss: 14.9484 - val_accuracy: 0.3151
Epoch 9659/10000
1/1 [==============================] - 0s 104ms/step - loss: 1.7619e-06 - accuracy: 1.0000 - val_loss: 14.9493 - val_accuracy: 0.3151
Epoch 9660/10000
1/1 [==============================] - 0s 103ms/step - loss: 1.7619e-06 - accuracy: 1.0000 - val_loss: 14.9486 - val_accuracy: 0.3152
Epoch 9661/10000
1/1 [==============================] - 0s 104ms/step - loss: 1.7598e-06 - accuracy: 1.0000 - val_loss: 14.9484 - val_accuracy: 0.3151
Epoch 9662/10000
1/1 [==============================] - 0s 100ms/step - loss: 1.7583e-06 - accuracy: 1.0000 - val_loss: 14.9490 - val_accuracy: 0.3151
Epoch 9663/10000
1/1 [==============================] - 0s 101ms/step - loss: 1.7567e-06 - accuracy: 1.0000 - val_loss: 14.9501 - val_accuracy: 0.3151
Epoch 9664/10000
1/1 [==============================] - 0s 98ms/step - loss: 1.7552e-06 - accuracy: 1.0000 - val_loss: 14.9519 - val_accuracy: 0.3152
Epoch 9665/10000
1/1 [==============================] - 0s 102ms/step - loss: 1.7562e-06 - accuracy: 1.0000 - val_loss: 14.9531 - val_accuracy: 0.3152
Epoch 9666/10000
1/1 [==============================] - 0s 99ms/step - loss: 1.7571e-06 - accuracy: 1.0000 - val_loss: 14.9527 - val_accuracy: 0.3152
Epoch 9667/10000
1/1 [==============================] - 0s 101ms/step - loss: 1.7543e-06 - accuracy: 1.0000 - val_loss: 14.9524 - val_accuracy: 0.3152
Epoch 9668/10000
1/1 [==============================] - 0s 103ms/step - loss: 1.7512e-06 - accuracy: 1.0000 - val_loss: 14.9529 - val_accuracy: 0.3152
Epoch 9669/10000
1/1 [==============================] - 0s 99ms/step - loss: 1.7493e-06 - accuracy: 1.0000 - val_loss: 14.9538 - val_accuracy: 0.3152
Epoch 9670/10000
1/1 [==============================] - 0s 101ms/step - loss: 1.7488e-06 - accuracy: 1.0000 - val_loss: 14.9547 - val_accuracy: 0.3152
Epoch 9671/10000
1/1 [==============================] - 0s 103ms/step - loss: 1.7474e-06 - accuracy: 1.0000 - val_loss: 14.9558 - val_accuracy: 0.3152
Epoch 9672/10000
1/1 [==============================] - 0s 107ms/step - loss: 1.7459e-06 - accuracy: 1.0000 - val_loss: 14.9564 - val_accuracy: 0.3151
Epoch 9673/10000
1/1 [==============================] - 0s 102ms/step - loss: 1.7462e-06 - accuracy: 1.0000 - val_loss: 14.9564 - val_accuracy: 0.3151
Epoch 9674/10000
1/1 [==============================] - 0s 99ms/step - loss: 1.7438e-06 - accuracy: 1.0000 - val_loss: 14.9563 - val_accuracy: 0.3153
Epoch 9675/10000
1/1 [==============================] - 0s 104ms/step - loss: 1.7452e-06 - accuracy: 1.0000 - val_loss: 14.9573 - val_accuracy: 0.3153
Epoch 9676/10000
1/1 [==============================] - 0s 101ms/step - loss: 1.7443e-06 - accuracy: 1.0000 - val_loss: 14.9584 - val_accuracy: 0.3152
Epoch 9677/10000
1/1 [==============================] - 0s 101ms/step - loss: 1.7414e-06 - accuracy: 1.0000 - val_loss: 14.9593 - val_accuracy: 0.3151
Epoch 9678/10000
1/1 [==============================] - 0s 98ms/step - loss: 1.7395e-06 - accuracy: 1.0000 - val_loss: 14.9593 - val_accuracy: 0.3152
Epoch 9679/10000
1/1 [==============================] - 0s 105ms/step - loss: 1.7397e-06 - accuracy: 1.0000 - val_loss: 14.9596 - val_accuracy: 0.3152
Epoch 9680/10000
1/1 [==============================] - 0s 103ms/step - loss: 1.7402e-06 - accuracy: 1.0000 - val_loss: 14.9605 - val_accuracy: 0.3152
Epoch 9681/10000
1/1 [==============================] - 0s 98ms/step - loss: 1.7376e-06 - accuracy: 1.0000 - val_loss: 14.9615 - val_accuracy: 0.3152
Epoch 9682/10000
1/1 [==============================] - 0s 102ms/step - loss: 1.7378e-06 - accuracy: 1.0000 - val_loss: 14.9618 - val_accuracy: 0.3151
Epoch 9683/10000
1/1 [==============================] - 0s 100ms/step - loss: 1.7362e-06 - accuracy: 1.0000 - val_loss: 14.9617 - val_accuracy: 0.3152
Epoch 9684/10000
1/1 [==============================] - 0s 102ms/step - loss: 1.7345e-06 - accuracy: 1.0000 - val_loss: 14.9619 - val_accuracy: 0.3152
Epoch 9685/10000
1/1 [==============================] - 0s 100ms/step - loss: 1.7352e-06 - accuracy: 1.0000 - val_loss: 14.9635 - val_accuracy: 0.3152
Epoch 9686/10000
1/1 [==============================] - 0s 103ms/step - loss: 1.7333e-06 - accuracy: 1.0000 - val_loss: 14.9647 - val_accuracy: 0.3151
Epoch 9687/10000
1/1 [==============================] - 0s 104ms/step - loss: 1.7328e-06 - accuracy: 1.0000 - val_loss: 14.9647 - val_accuracy: 0.3152
Epoch 9688/10000
1/1 [==============================] - 0s 101ms/step - loss: 1.7309e-06 - accuracy: 1.0000 - val_loss: 14.9642 - val_accuracy: 0.3150
Epoch 9689/10000
1/1 [==============================] - 0s 105ms/step - loss: 1.7316e-06 - accuracy: 1.0000 - val_loss: 14.9644 - val_accuracy: 0.3151
Epoch 9690/10000
1/1 [==============================] - 0s 101ms/step - loss: 1.7316e-06 - accuracy: 1.0000 - val_loss: 14.9652 - val_accuracy: 0.3150
Epoch 9691/10000
1/1 [==============================] - 0s 100ms/step - loss: 1.7307e-06 - accuracy: 1.0000 - val_loss: 14.9663 - val_accuracy: 0.3151
Epoch 9692/10000
1/1 [==============================] - 0s 99ms/step - loss: 1.7281e-06 - accuracy: 1.0000 - val_loss: 14.9672 - val_accuracy: 0.3152
Epoch 9693/10000
1/1 [==============================] - 0s 103ms/step - loss: 1.7283e-06 - accuracy: 1.0000 - val_loss: 14.9682 - val_accuracy: 0.3152
Epoch 9694/10000
1/1 [==============================] - 0s 102ms/step - loss: 1.7266e-06 - accuracy: 1.0000 - val_loss: 14.9685 - val_accuracy: 0.3151
Epoch 9695/10000
1/1 [==============================] - 0s 102ms/step - loss: 1.7257e-06 - accuracy: 1.0000 - val_loss: 14.9689 - val_accuracy: 0.3151
Epoch 9696/10000
1/1 [==============================] - 0s 105ms/step - loss: 1.7250e-06 - accuracy: 1.0000 - val_loss: 14.9696 - val_accuracy: 0.3153
Epoch 9697/10000
1/1 [==============================] - 0s 100ms/step - loss: 1.7250e-06 - accuracy: 1.0000 - val_loss: 14.9705 - val_accuracy: 0.3153
Epoch 9698/10000
1/1 [==============================] - 0s 103ms/step - loss: 1.7228e-06 - accuracy: 1.0000 - val_loss: 14.9714 - val_accuracy: 0.3152
Epoch 9699/10000
1/1 [==============================] - 0s 112ms/step - loss: 1.7219e-06 - accuracy: 1.0000 - val_loss: 14.9718 - val_accuracy: 0.3152
Epoch 9700/10000
1/1 [==============================] - 0s 103ms/step - loss: 1.7209e-06 - accuracy: 1.0000 - val_loss: 14.9720 - val_accuracy: 0.3152
Epoch 9701/10000
1/1 [==============================] - 0s 109ms/step - loss: 1.7197e-06 - accuracy: 1.0000 - val_loss: 14.9721 - val_accuracy: 0.3152
Epoch 9702/10000
1/1 [==============================] - 0s 104ms/step - loss: 1.7180e-06 - accuracy: 1.0000 - val_loss: 14.9729 - val_accuracy: 0.3152
Epoch 9703/10000
1/1 [==============================] - 0s 101ms/step - loss: 1.7178e-06 - accuracy: 1.0000 - val_loss: 14.9734 - val_accuracy: 0.3151
Epoch 9704/10000
1/1 [==============================] - 0s 106ms/step - loss: 1.7166e-06 - accuracy: 1.0000 - val_loss: 14.9743 - val_accuracy: 0.3152
Epoch 9705/10000
1/1 [==============================] - 0s 108ms/step - loss: 1.7168e-06 - accuracy: 1.0000 - val_loss: 14.9749 - val_accuracy: 0.3154
Epoch 9706/10000
1/1 [==============================] - 0s 105ms/step - loss: 1.7168e-06 - accuracy: 1.0000 - val_loss: 14.9758 - val_accuracy: 0.3154
Epoch 9707/10000
1/1 [==============================] - 0s 109ms/step - loss: 1.7154e-06 - accuracy: 1.0000 - val_loss: 14.9761 - val_accuracy: 0.3151
Epoch 9708/10000
1/1 [==============================] - 0s 100ms/step - loss: 1.7137e-06 - accuracy: 1.0000 - val_loss: 14.9756 - val_accuracy: 0.3151
Epoch 9709/10000
1/1 [==============================] - 0s 104ms/step - loss: 1.7123e-06 - accuracy: 1.0000 - val_loss: 14.9754 - val_accuracy: 0.3152
Epoch 9710/10000
1/1 [==============================] - 0s 107ms/step - loss: 1.7118e-06 - accuracy: 1.0000 - val_loss: 14.9765 - val_accuracy: 0.3152
Epoch 9711/10000
1/1 [==============================] - 0s 103ms/step - loss: 1.7102e-06 - accuracy: 1.0000 - val_loss: 14.9782 - val_accuracy: 0.3151
Epoch 9712/10000
1/1 [==============================] - 0s 106ms/step - loss: 1.7090e-06 - accuracy: 1.0000 - val_loss: 14.9798 - val_accuracy: 0.3151
Epoch 9713/10000
1/1 [==============================] - 0s 108ms/step - loss: 1.7080e-06 - accuracy: 1.0000 - val_loss: 14.9801 - val_accuracy: 0.3152
Epoch 9714/10000
1/1 [==============================] - 0s 108ms/step - loss: 1.7090e-06 - accuracy: 1.0000 - val_loss: 14.9795 - val_accuracy: 0.3152
Epoch 9715/10000
1/1 [==============================] - 0s 105ms/step - loss: 1.7087e-06 - accuracy: 1.0000 - val_loss: 14.9795 - val_accuracy: 0.3152
Epoch 9716/10000
1/1 [==============================] - 0s 114ms/step - loss: 1.7080e-06 - accuracy: 1.0000 - val_loss: 14.9803 - val_accuracy: 0.3151
Epoch 9717/10000
1/1 [==============================] - 0s 107ms/step - loss: 1.7056e-06 - accuracy: 1.0000 - val_loss: 14.9817 - val_accuracy: 0.3152
Epoch 9718/10000
1/1 [==============================] - 0s 110ms/step - loss: 1.7052e-06 - accuracy: 1.0000 - val_loss: 14.9829 - val_accuracy: 0.3153
Epoch 9719/10000
1/1 [==============================] - 0s 109ms/step - loss: 1.7052e-06 - accuracy: 1.0000 - val_loss: 14.9828 - val_accuracy: 0.3153
Epoch 9720/10000
1/1 [==============================] - 0s 106ms/step - loss: 1.7014e-06 - accuracy: 1.0000 - val_loss: 14.9830 - val_accuracy: 0.3153
Epoch 9721/10000
1/1 [==============================] - 0s 116ms/step - loss: 1.7004e-06 - accuracy: 1.0000 - val_loss: 14.9835 - val_accuracy: 0.3153
Epoch 9722/10000
1/1 [==============================] - 0s 104ms/step - loss: 1.7006e-06 - accuracy: 1.0000 - val_loss: 14.9848 - val_accuracy: 0.3152
Epoch 9723/10000
1/1 [==============================] - 0s 106ms/step - loss: 1.7006e-06 - accuracy: 1.0000 - val_loss: 14.9858 - val_accuracy: 0.3152
Epoch 9724/10000
1/1 [==============================] - 0s 106ms/step - loss: 1.7002e-06 - accuracy: 1.0000 - val_loss: 14.9861 - val_accuracy: 0.3152
Epoch 9725/10000
1/1 [==============================] - 0s 105ms/step - loss: 1.6987e-06 - accuracy: 1.0000 - val_loss: 14.9862 - val_accuracy: 0.3152
Epoch 9726/10000
1/1 [==============================] - 0s 106ms/step - loss: 1.6971e-06 - accuracy: 1.0000 - val_loss: 14.9867 - val_accuracy: 0.3152
Epoch 9727/10000
1/1 [==============================] - 0s 103ms/step - loss: 1.6942e-06 - accuracy: 1.0000 - val_loss: 14.9872 - val_accuracy: 0.3153
Epoch 9728/10000
1/1 [==============================] - 0s 110ms/step - loss: 1.6942e-06 - accuracy: 1.0000 - val_loss: 14.9883 - val_accuracy: 0.3153
Epoch 9729/10000
1/1 [==============================] - 0s 110ms/step - loss: 1.6947e-06 - accuracy: 1.0000 - val_loss: 14.9887 - val_accuracy: 0.3153
Epoch 9730/10000
1/1 [==============================] - 0s 112ms/step - loss: 1.6913e-06 - accuracy: 1.0000 - val_loss: 14.9890 - val_accuracy: 0.3153
Epoch 9731/10000
1/1 [==============================] - 0s 109ms/step - loss: 1.6928e-06 - accuracy: 1.0000 - val_loss: 14.9897 - val_accuracy: 0.3152
Epoch 9732/10000
1/1 [==============================] - 0s 104ms/step - loss: 1.6904e-06 - accuracy: 1.0000 - val_loss: 14.9905 - val_accuracy: 0.3153
Epoch 9733/10000
1/1 [==============================] - 0s 111ms/step - loss: 1.6894e-06 - accuracy: 1.0000 - val_loss: 14.9909 - val_accuracy: 0.3153
Epoch 9734/10000
1/1 [==============================] - 0s 103ms/step - loss: 1.6890e-06 - accuracy: 1.0000 - val_loss: 14.9911 - val_accuracy: 0.3152
Epoch 9735/10000
1/1 [==============================] - 0s 102ms/step - loss: 1.6875e-06 - accuracy: 1.0000 - val_loss: 14.9917 - val_accuracy: 0.3152
Epoch 9736/10000
1/1 [==============================] - 0s 107ms/step - loss: 1.6866e-06 - accuracy: 1.0000 - val_loss: 14.9925 - val_accuracy: 0.3151
Epoch 9737/10000
1/1 [==============================] - 0s 105ms/step - loss: 1.6863e-06 - accuracy: 1.0000 - val_loss: 14.9935 - val_accuracy: 0.3151
Epoch 9738/10000
1/1 [==============================] - 0s 104ms/step - loss: 1.6866e-06 - accuracy: 1.0000 - val_loss: 14.9940 - val_accuracy: 0.3153
Epoch 9739/10000
1/1 [==============================] - 0s 110ms/step - loss: 1.6842e-06 - accuracy: 1.0000 - val_loss: 14.9944 - val_accuracy: 0.3152
Epoch 9740/10000
1/1 [==============================] - 0s 103ms/step - loss: 1.6832e-06 - accuracy: 1.0000 - val_loss: 14.9952 - val_accuracy: 0.3151
Epoch 9741/10000
1/1 [==============================] - 0s 110ms/step - loss: 1.6823e-06 - accuracy: 1.0000 - val_loss: 14.9952 - val_accuracy: 0.3153
Epoch 9742/10000
1/1 [==============================] - 0s 104ms/step - loss: 1.6813e-06 - accuracy: 1.0000 - val_loss: 14.9958 - val_accuracy: 0.3153
Epoch 9743/10000
1/1 [==============================] - 0s 103ms/step - loss: 1.6811e-06 - accuracy: 1.0000 - val_loss: 14.9965 - val_accuracy: 0.3151
Epoch 9744/10000
1/1 [==============================] - 0s 104ms/step - loss: 1.6797e-06 - accuracy: 1.0000 - val_loss: 14.9968 - val_accuracy: 0.3152
Epoch 9745/10000
1/1 [==============================] - 0s 110ms/step - loss: 1.6789e-06 - accuracy: 1.0000 - val_loss: 14.9971 - val_accuracy: 0.3152
Epoch 9746/10000
1/1 [==============================] - 0s 108ms/step - loss: 1.6777e-06 - accuracy: 1.0000 - val_loss: 14.9982 - val_accuracy: 0.3152
Epoch 9747/10000
1/1 [==============================] - 0s 101ms/step - loss: 1.6770e-06 - accuracy: 1.0000 - val_loss: 14.9993 - val_accuracy: 0.3153
Epoch 9748/10000
1/1 [==============================] - 0s 108ms/step - loss: 1.6768e-06 - accuracy: 1.0000 - val_loss: 14.9989 - val_accuracy: 0.3152
Epoch 9749/10000
1/1 [==============================] - 0s 99ms/step - loss: 1.6746e-06 - accuracy: 1.0000 - val_loss: 14.9994 - val_accuracy: 0.3152
Epoch 9750/10000
1/1 [==============================] - 0s 104ms/step - loss: 1.6730e-06 - accuracy: 1.0000 - val_loss: 14.9999 - val_accuracy: 0.3152
Epoch 9751/10000
1/1 [==============================] - 0s 107ms/step - loss: 1.6718e-06 - accuracy: 1.0000 - val_loss: 15.0005 - val_accuracy: 0.3152
Epoch 9752/10000
1/1 [==============================] - 0s 107ms/step - loss: 1.6708e-06 - accuracy: 1.0000 - val_loss: 15.0016 - val_accuracy: 0.3152
Epoch 9753/10000
1/1 [==============================] - 0s 105ms/step - loss: 1.6699e-06 - accuracy: 1.0000 - val_loss: 15.0026 - val_accuracy: 0.3152
Epoch 9754/10000
1/1 [==============================] - 0s 103ms/step - loss: 1.6689e-06 - accuracy: 1.0000 - val_loss: 15.0027 - val_accuracy: 0.3152
Epoch 9755/10000
1/1 [==============================] - 0s 105ms/step - loss: 1.6684e-06 - accuracy: 1.0000 - val_loss: 15.0028 - val_accuracy: 0.3152
Epoch 9756/10000
1/1 [==============================] - 0s 102ms/step - loss: 1.6684e-06 - accuracy: 1.0000 - val_loss: 15.0033 - val_accuracy: 0.3151
Epoch 9757/10000
1/1 [==============================] - 0s 103ms/step - loss: 1.6668e-06 - accuracy: 1.0000 - val_loss: 15.0037 - val_accuracy: 0.3152
Epoch 9758/10000
1/1 [==============================] - 0s 108ms/step - loss: 1.6651e-06 - accuracy: 1.0000 - val_loss: 15.0046 - val_accuracy: 0.3152
Epoch 9759/10000
1/1 [==============================] - 0s 107ms/step - loss: 1.6642e-06 - accuracy: 1.0000 - val_loss: 15.0057 - val_accuracy: 0.3152
Epoch 9760/10000
1/1 [==============================] - 0s 102ms/step - loss: 1.6644e-06 - accuracy: 1.0000 - val_loss: 15.0060 - val_accuracy: 0.3152
Epoch 9761/10000
1/1 [==============================] - 0s 100ms/step - loss: 1.6637e-06 - accuracy: 1.0000 - val_loss: 15.0066 - val_accuracy: 0.3152
Epoch 9762/10000
1/1 [==============================] - 0s 108ms/step - loss: 1.6627e-06 - accuracy: 1.0000 - val_loss: 15.0072 - val_accuracy: 0.3152
Epoch 9763/10000
1/1 [==============================] - 0s 104ms/step - loss: 1.6615e-06 - accuracy: 1.0000 - val_loss: 15.0078 - val_accuracy: 0.3153
Epoch 9764/10000
1/1 [==============================] - 0s 106ms/step - loss: 1.6603e-06 - accuracy: 1.0000 - val_loss: 15.0082 - val_accuracy: 0.3153
Epoch 9765/10000
1/1 [==============================] - 0s 101ms/step - loss: 1.6592e-06 - accuracy: 1.0000 - val_loss: 15.0088 - val_accuracy: 0.3152
Epoch 9766/10000
1/1 [==============================] - 0s 106ms/step - loss: 1.6580e-06 - accuracy: 1.0000 - val_loss: 15.0095 - val_accuracy: 0.3152
Epoch 9767/10000
1/1 [==============================] - 0s 104ms/step - loss: 1.6572e-06 - accuracy: 1.0000 - val_loss: 15.0103 - val_accuracy: 0.3152
Epoch 9768/10000
1/1 [==============================] - 0s 98ms/step - loss: 1.6563e-06 - accuracy: 1.0000 - val_loss: 15.0104 - val_accuracy: 0.3152
Epoch 9769/10000
1/1 [==============================] - 0s 113ms/step - loss: 1.6561e-06 - accuracy: 1.0000 - val_loss: 15.0112 - val_accuracy: 0.3152
Epoch 9770/10000
1/1 [==============================] - 0s 103ms/step - loss: 1.6556e-06 - accuracy: 1.0000 - val_loss: 15.0118 - val_accuracy: 0.3152
Epoch 9771/10000
1/1 [==============================] - 0s 105ms/step - loss: 1.6549e-06 - accuracy: 1.0000 - val_loss: 15.0124 - val_accuracy: 0.3152
Epoch 9772/10000
1/1 [==============================] - 0s 106ms/step - loss: 1.6546e-06 - accuracy: 1.0000 - val_loss: 15.0131 - val_accuracy: 0.3152
Epoch 9773/10000
1/1 [==============================] - 0s 99ms/step - loss: 1.6532e-06 - accuracy: 1.0000 - val_loss: 15.0134 - val_accuracy: 0.3152
Epoch 9774/10000
1/1 [==============================] - 0s 102ms/step - loss: 1.6506e-06 - accuracy: 1.0000 - val_loss: 15.0141 - val_accuracy: 0.3152
Epoch 9775/10000
1/1 [==============================] - 0s 101ms/step - loss: 1.6508e-06 - accuracy: 1.0000 - val_loss: 15.0146 - val_accuracy: 0.3152
Epoch 9776/10000
1/1 [==============================] - 0s 104ms/step - loss: 1.6508e-06 - accuracy: 1.0000 - val_loss: 15.0151 - val_accuracy: 0.3152
Epoch 9777/10000
1/1 [==============================] - 0s 101ms/step - loss: 1.6487e-06 - accuracy: 1.0000 - val_loss: 15.0155 - val_accuracy: 0.3152
Epoch 9778/10000
1/1 [==============================] - 0s 101ms/step - loss: 1.6489e-06 - accuracy: 1.0000 - val_loss: 15.0163 - val_accuracy: 0.3152
Epoch 9779/10000
1/1 [==============================] - 0s 105ms/step - loss: 1.6475e-06 - accuracy: 1.0000 - val_loss: 15.0173 - val_accuracy: 0.3152
Epoch 9780/10000
1/1 [==============================] - 0s 106ms/step - loss: 1.6472e-06 - accuracy: 1.0000 - val_loss: 15.0176 - val_accuracy: 0.3152
Epoch 9781/10000
1/1 [==============================] - 0s 104ms/step - loss: 1.6472e-06 - accuracy: 1.0000 - val_loss: 15.0175 - val_accuracy: 0.3152
Epoch 9782/10000
1/1 [==============================] - 0s 99ms/step - loss: 1.6468e-06 - accuracy: 1.0000 - val_loss: 15.0179 - val_accuracy: 0.3152
Epoch 9783/10000
1/1 [==============================] - 0s 99ms/step - loss: 1.6434e-06 - accuracy: 1.0000 - val_loss: 15.0194 - val_accuracy: 0.3152
Epoch 9784/10000
1/1 [==============================] - 0s 99ms/step - loss: 1.6441e-06 - accuracy: 1.0000 - val_loss: 15.0200 - val_accuracy: 0.3152
Epoch 9785/10000
1/1 [==============================] - 0s 107ms/step - loss: 1.6425e-06 - accuracy: 1.0000 - val_loss: 15.0202 - val_accuracy: 0.3152
Epoch 9786/10000
1/1 [==============================] - 0s 100ms/step - loss: 1.6434e-06 - accuracy: 1.0000 - val_loss: 15.0205 - val_accuracy: 0.3152
Epoch 9787/10000
1/1 [==============================] - 0s 100ms/step - loss: 1.6420e-06 - accuracy: 1.0000 - val_loss: 15.0215 - val_accuracy: 0.3152
Epoch 9788/10000
1/1 [==============================] - 0s 100ms/step - loss: 1.6401e-06 - accuracy: 1.0000 - val_loss: 15.0222 - val_accuracy: 0.3152
Epoch 9789/10000
1/1 [==============================] - 0s 101ms/step - loss: 1.6403e-06 - accuracy: 1.0000 - val_loss: 15.0229 - val_accuracy: 0.3152
Epoch 9790/10000
1/1 [==============================] - 0s 107ms/step - loss: 1.6384e-06 - accuracy: 1.0000 - val_loss: 15.0231 - val_accuracy: 0.3152
Epoch 9791/10000
1/1 [==============================] - 0s 100ms/step - loss: 1.6375e-06 - accuracy: 1.0000 - val_loss: 15.0232 - val_accuracy: 0.3152
Epoch 9792/10000
1/1 [==============================] - 0s 99ms/step - loss: 1.6351e-06 - accuracy: 1.0000 - val_loss: 15.0236 - val_accuracy: 0.3151
Epoch 9793/10000
1/1 [==============================] - 0s 109ms/step - loss: 1.6348e-06 - accuracy: 1.0000 - val_loss: 15.0248 - val_accuracy: 0.3151
Epoch 9794/10000
1/1 [==============================] - 0s 109ms/step - loss: 1.6346e-06 - accuracy: 1.0000 - val_loss: 15.0263 - val_accuracy: 0.3151
Epoch 9795/10000
1/1 [==============================] - 0s 107ms/step - loss: 1.6341e-06 - accuracy: 1.0000 - val_loss: 15.0271 - val_accuracy: 0.3152
Epoch 9796/10000
1/1 [==============================] - 0s 102ms/step - loss: 1.6310e-06 - accuracy: 1.0000 - val_loss: 15.0273 - val_accuracy: 0.3152
Epoch 9797/10000
1/1 [==============================] - 0s 102ms/step - loss: 1.6301e-06 - accuracy: 1.0000 - val_loss: 15.0264 - val_accuracy: 0.3152
Epoch 9798/10000
1/1 [==============================] - 0s 99ms/step - loss: 1.6303e-06 - accuracy: 1.0000 - val_loss: 15.0264 - val_accuracy: 0.3152
Epoch 9799/10000
1/1 [==============================] - 0s 100ms/step - loss: 1.6303e-06 - accuracy: 1.0000 - val_loss: 15.0270 - val_accuracy: 0.3151
Epoch 9800/10000
1/1 [==============================] - 0s 103ms/step - loss: 1.6289e-06 - accuracy: 1.0000 - val_loss: 15.0279 - val_accuracy: 0.3151
Epoch 9801/10000
1/1 [==============================] - 0s 102ms/step - loss: 1.6267e-06 - accuracy: 1.0000 - val_loss: 15.0289 - val_accuracy: 0.3152
Epoch 9802/10000
1/1 [==============================] - 0s 105ms/step - loss: 1.6260e-06 - accuracy: 1.0000 - val_loss: 15.0299 - val_accuracy: 0.3151
Epoch 9803/10000
1/1 [==============================] - 0s 103ms/step - loss: 1.6243e-06 - accuracy: 1.0000 - val_loss: 15.0309 - val_accuracy: 0.3152
Epoch 9804/10000
1/1 [==============================] - 0s 106ms/step - loss: 1.6239e-06 - accuracy: 1.0000 - val_loss: 15.0312 - val_accuracy: 0.3152
Epoch 9805/10000
1/1 [==============================] - 0s 102ms/step - loss: 1.6246e-06 - accuracy: 1.0000 - val_loss: 15.0314 - val_accuracy: 0.3152
Epoch 9806/10000
1/1 [==============================] - 0s 99ms/step - loss: 1.6227e-06 - accuracy: 1.0000 - val_loss: 15.0316 - val_accuracy: 0.3152
Epoch 9807/10000
1/1 [==============================] - 0s 103ms/step - loss: 1.6217e-06 - accuracy: 1.0000 - val_loss: 15.0322 - val_accuracy: 0.3152
Epoch 9808/10000
1/1 [==============================] - 0s 102ms/step - loss: 1.6201e-06 - accuracy: 1.0000 - val_loss: 15.0332 - val_accuracy: 0.3152
Epoch 9809/10000
1/1 [==============================] - 0s 102ms/step - loss: 1.6189e-06 - accuracy: 1.0000 - val_loss: 15.0342 - val_accuracy: 0.3152
Epoch 9810/10000
1/1 [==============================] - 0s 98ms/step - loss: 1.6179e-06 - accuracy: 1.0000 - val_loss: 15.0345 - val_accuracy: 0.3152
Epoch 9811/10000
1/1 [==============================] - 0s 101ms/step - loss: 1.6167e-06 - accuracy: 1.0000 - val_loss: 15.0348 - val_accuracy: 0.3152
Epoch 9812/10000
1/1 [==============================] - 0s 101ms/step - loss: 1.6160e-06 - accuracy: 1.0000 - val_loss: 15.0354 - val_accuracy: 0.3152
Epoch 9813/10000
1/1 [==============================] - 0s 100ms/step - loss: 1.6162e-06 - accuracy: 1.0000 - val_loss: 15.0359 - val_accuracy: 0.3152
Epoch 9814/10000
1/1 [==============================] - 0s 102ms/step - loss: 1.6150e-06 - accuracy: 1.0000 - val_loss: 15.0366 - val_accuracy: 0.3152
Epoch 9815/10000
1/1 [==============================] - 0s 99ms/step - loss: 1.6119e-06 - accuracy: 1.0000 - val_loss: 15.0378 - val_accuracy: 0.3152
Epoch 9816/10000
1/1 [==============================] - 0s 100ms/step - loss: 1.6098e-06 - accuracy: 1.0000 - val_loss: 15.0383 - val_accuracy: 0.3152
Epoch 9817/10000
1/1 [==============================] - 0s 105ms/step - loss: 1.6096e-06 - accuracy: 1.0000 - val_loss: 15.0382 - val_accuracy: 0.3152
Epoch 9818/10000
1/1 [==============================] - 0s 101ms/step - loss: 1.6105e-06 - accuracy: 1.0000 - val_loss: 15.0382 - val_accuracy: 0.3152
Epoch 9819/10000
1/1 [==============================] - 0s 103ms/step - loss: 1.6091e-06 - accuracy: 1.0000 - val_loss: 15.0393 - val_accuracy: 0.3152
Epoch 9820/10000
1/1 [==============================] - 0s 102ms/step - loss: 1.6098e-06 - accuracy: 1.0000 - val_loss: 15.0408 - val_accuracy: 0.3152
Epoch 9821/10000
1/1 [==============================] - 0s 107ms/step - loss: 1.6069e-06 - accuracy: 1.0000 - val_loss: 15.0416 - val_accuracy: 0.3152
Epoch 9822/10000
1/1 [==============================] - 0s 103ms/step - loss: 1.6043e-06 - accuracy: 1.0000 - val_loss: 15.0414 - val_accuracy: 0.3152
Epoch 9823/10000
1/1 [==============================] - 0s 103ms/step - loss: 1.6024e-06 - accuracy: 1.0000 - val_loss: 15.0413 - val_accuracy: 0.3152
Epoch 9824/10000
1/1 [==============================] - 0s 102ms/step - loss: 1.6017e-06 - accuracy: 1.0000 - val_loss: 15.0418 - val_accuracy: 0.3152
Epoch 9825/10000
1/1 [==============================] - 0s 111ms/step - loss: 1.6005e-06 - accuracy: 1.0000 - val_loss: 15.0428 - val_accuracy: 0.3152
Epoch 9826/10000
1/1 [==============================] - 0s 104ms/step - loss: 1.5979e-06 - accuracy: 1.0000 - val_loss: 15.0442 - val_accuracy: 0.3152
Epoch 9827/10000
1/1 [==============================] - 0s 105ms/step - loss: 1.5986e-06 - accuracy: 1.0000 - val_loss: 15.0449 - val_accuracy: 0.3152
Epoch 9828/10000
1/1 [==============================] - 0s 103ms/step - loss: 1.5981e-06 - accuracy: 1.0000 - val_loss: 15.0449 - val_accuracy: 0.3152
Epoch 9829/10000
1/1 [==============================] - 0s 107ms/step - loss: 1.5962e-06 - accuracy: 1.0000 - val_loss: 15.0451 - val_accuracy: 0.3152
Epoch 9830/10000
1/1 [==============================] - 0s 107ms/step - loss: 1.5960e-06 - accuracy: 1.0000 - val_loss: 15.0452 - val_accuracy: 0.3152
Epoch 9831/10000
1/1 [==============================] - 0s 112ms/step - loss: 1.5955e-06 - accuracy: 1.0000 - val_loss: 15.0460 - val_accuracy: 0.3152
Epoch 9832/10000
1/1 [==============================] - 0s 107ms/step - loss: 1.5933e-06 - accuracy: 1.0000 - val_loss: 15.0468 - val_accuracy: 0.3152
Epoch 9833/10000
1/1 [==============================] - 0s 106ms/step - loss: 1.5922e-06 - accuracy: 1.0000 - val_loss: 15.0473 - val_accuracy: 0.3151
Epoch 9834/10000
1/1 [==============================] - 0s 106ms/step - loss: 1.5917e-06 - accuracy: 1.0000 - val_loss: 15.0484 - val_accuracy: 0.3151
Epoch 9835/10000
1/1 [==============================] - 0s 103ms/step - loss: 1.5917e-06 - accuracy: 1.0000 - val_loss: 15.0490 - val_accuracy: 0.3151
Epoch 9836/10000
1/1 [==============================] - 0s 101ms/step - loss: 1.5919e-06 - accuracy: 1.0000 - val_loss: 15.0488 - val_accuracy: 0.3152
Epoch 9837/10000
1/1 [==============================] - 0s 114ms/step - loss: 1.5914e-06 - accuracy: 1.0000 - val_loss: 15.0489 - val_accuracy: 0.3152
Epoch 9838/10000
1/1 [==============================] - 0s 107ms/step - loss: 1.5907e-06 - accuracy: 1.0000 - val_loss: 15.0497 - val_accuracy: 0.3151
Epoch 9839/10000
1/1 [==============================] - 0s 107ms/step - loss: 1.5891e-06 - accuracy: 1.0000 - val_loss: 15.0508 - val_accuracy: 0.3152
Epoch 9840/10000
1/1 [==============================] - 0s 112ms/step - loss: 1.5867e-06 - accuracy: 1.0000 - val_loss: 15.0518 - val_accuracy: 0.3152
Epoch 9841/10000
1/1 [==============================] - 0s 112ms/step - loss: 1.5867e-06 - accuracy: 1.0000 - val_loss: 15.0529 - val_accuracy: 0.3151
Epoch 9842/10000
1/1 [==============================] - 0s 106ms/step - loss: 1.5871e-06 - accuracy: 1.0000 - val_loss: 15.0531 - val_accuracy: 0.3152
Epoch 9843/10000
1/1 [==============================] - 0s 115ms/step - loss: 1.5845e-06 - accuracy: 1.0000 - val_loss: 15.0533 - val_accuracy: 0.3151
Epoch 9844/10000
1/1 [==============================] - 0s 113ms/step - loss: 1.5836e-06 - accuracy: 1.0000 - val_loss: 15.0533 - val_accuracy: 0.3151
Epoch 9845/10000
1/1 [==============================] - 0s 106ms/step - loss: 1.5831e-06 - accuracy: 1.0000 - val_loss: 15.0543 - val_accuracy: 0.3152
Epoch 9846/10000
1/1 [==============================] - 0s 104ms/step - loss: 1.5821e-06 - accuracy: 1.0000 - val_loss: 15.0550 - val_accuracy: 0.3152
Epoch 9847/10000
1/1 [==============================] - 0s 108ms/step - loss: 1.5819e-06 - accuracy: 1.0000 - val_loss: 15.0560 - val_accuracy: 0.3151
Epoch 9848/10000
1/1 [==============================] - 0s 105ms/step - loss: 1.5819e-06 - accuracy: 1.0000 - val_loss: 15.0570 - val_accuracy: 0.3152
Epoch 9849/10000
1/1 [==============================] - 0s 110ms/step - loss: 1.5776e-06 - accuracy: 1.0000 - val_loss: 15.0570 - val_accuracy: 0.3151
Epoch 9850/10000
1/1 [==============================] - 0s 101ms/step - loss: 1.5779e-06 - accuracy: 1.0000 - val_loss: 15.0568 - val_accuracy: 0.3151
Epoch 9851/10000
1/1 [==============================] - 0s 105ms/step - loss: 1.5767e-06 - accuracy: 1.0000 - val_loss: 15.0576 - val_accuracy: 0.3151
Epoch 9852/10000
1/1 [==============================] - 0s 100ms/step - loss: 1.5762e-06 - accuracy: 1.0000 - val_loss: 15.0587 - val_accuracy: 0.3152
Epoch 9853/10000
1/1 [==============================] - 0s 102ms/step - loss: 1.5762e-06 - accuracy: 1.0000 - val_loss: 15.0596 - val_accuracy: 0.3152
Epoch 9854/10000
1/1 [==============================] - 0s 102ms/step - loss: 1.5748e-06 - accuracy: 1.0000 - val_loss: 15.0600 - val_accuracy: 0.3151
Epoch 9855/10000
1/1 [==============================] - 0s 109ms/step - loss: 1.5740e-06 - accuracy: 1.0000 - val_loss: 15.0600 - val_accuracy: 0.3151
Epoch 9856/10000
1/1 [==============================] - 0s 101ms/step - loss: 1.5714e-06 - accuracy: 1.0000 - val_loss: 15.0606 - val_accuracy: 0.3151
Epoch 9857/10000
1/1 [==============================] - 0s 100ms/step - loss: 1.5702e-06 - accuracy: 1.0000 - val_loss: 15.0613 - val_accuracy: 0.3151
Epoch 9858/10000
1/1 [==============================] - 0s 102ms/step - loss: 1.5714e-06 - accuracy: 1.0000 - val_loss: 15.0619 - val_accuracy: 0.3151
Epoch 9859/10000
1/1 [==============================] - 0s 99ms/step - loss: 1.5705e-06 - accuracy: 1.0000 - val_loss: 15.0629 - val_accuracy: 0.3151
Epoch 9860/10000
1/1 [==============================] - 0s 105ms/step - loss: 1.5688e-06 - accuracy: 1.0000 - val_loss: 15.0637 - val_accuracy: 0.3152
Epoch 9861/10000
1/1 [==============================] - 0s 110ms/step - loss: 1.5693e-06 - accuracy: 1.0000 - val_loss: 15.0636 - val_accuracy: 0.3152
Epoch 9862/10000
1/1 [==============================] - 0s 110ms/step - loss: 1.5674e-06 - accuracy: 1.0000 - val_loss: 15.0638 - val_accuracy: 0.3152
Epoch 9863/10000
1/1 [==============================] - 0s 109ms/step - loss: 1.5652e-06 - accuracy: 1.0000 - val_loss: 15.0648 - val_accuracy: 0.3151
Epoch 9864/10000
1/1 [==============================] - 0s 103ms/step - loss: 1.5643e-06 - accuracy: 1.0000 - val_loss: 15.0656 - val_accuracy: 0.3151
Epoch 9865/10000
1/1 [==============================] - 0s 105ms/step - loss: 1.5643e-06 - accuracy: 1.0000 - val_loss: 15.0658 - val_accuracy: 0.3152
Epoch 9866/10000
1/1 [==============================] - 0s 104ms/step - loss: 1.5643e-06 - accuracy: 1.0000 - val_loss: 15.0663 - val_accuracy: 0.3151
Epoch 9867/10000
1/1 [==============================] - 0s 110ms/step - loss: 1.5619e-06 - accuracy: 1.0000 - val_loss: 15.0675 - val_accuracy: 0.3151
Epoch 9868/10000
1/1 [==============================] - 0s 103ms/step - loss: 1.5621e-06 - accuracy: 1.0000 - val_loss: 15.0680 - val_accuracy: 0.3150
Epoch 9869/10000
1/1 [==============================] - 0s 105ms/step - loss: 1.5604e-06 - accuracy: 1.0000 - val_loss: 15.0680 - val_accuracy: 0.3152
Epoch 9870/10000
1/1 [==============================] - 0s 105ms/step - loss: 1.5588e-06 - accuracy: 1.0000 - val_loss: 15.0677 - val_accuracy: 0.3151
Epoch 9871/10000
1/1 [==============================] - 0s 100ms/step - loss: 1.5581e-06 - accuracy: 1.0000 - val_loss: 15.0685 - val_accuracy: 0.3152
Epoch 9872/10000
1/1 [==============================] - 0s 101ms/step - loss: 1.5578e-06 - accuracy: 1.0000 - val_loss: 15.0701 - val_accuracy: 0.3150
Epoch 9873/10000
1/1 [==============================] - 0s 102ms/step - loss: 1.5581e-06 - accuracy: 1.0000 - val_loss: 15.0711 - val_accuracy: 0.3150
Epoch 9874/10000
1/1 [==============================] - 0s 103ms/step - loss: 1.5576e-06 - accuracy: 1.0000 - val_loss: 15.0714 - val_accuracy: 0.3151
Epoch 9875/10000
1/1 [==============================] - 0s 105ms/step - loss: 1.5542e-06 - accuracy: 1.0000 - val_loss: 15.0716 - val_accuracy: 0.3152
Epoch 9876/10000
1/1 [==============================] - 0s 100ms/step - loss: 1.5540e-06 - accuracy: 1.0000 - val_loss: 15.0723 - val_accuracy: 0.3151
Epoch 9877/10000
1/1 [==============================] - 0s 101ms/step - loss: 1.5538e-06 - accuracy: 1.0000 - val_loss: 15.0731 - val_accuracy: 0.3151
Epoch 9878/10000
1/1 [==============================] - 0s 101ms/step - loss: 1.5521e-06 - accuracy: 1.0000 - val_loss: 15.0733 - val_accuracy: 0.3150
Epoch 9879/10000
1/1 [==============================] - 0s 102ms/step - loss: 1.5526e-06 - accuracy: 1.0000 - val_loss: 15.0731 - val_accuracy: 0.3150
Epoch 9880/10000
1/1 [==============================] - 0s 99ms/step - loss: 1.5516e-06 - accuracy: 1.0000 - val_loss: 15.0734 - val_accuracy: 0.3150
Epoch 9881/10000
1/1 [==============================] - 0s 102ms/step - loss: 1.5533e-06 - accuracy: 1.0000 - val_loss: 15.0747 - val_accuracy: 0.3151
Epoch 9882/10000
1/1 [==============================] - 0s 102ms/step - loss: 1.5519e-06 - accuracy: 1.0000 - val_loss: 15.0763 - val_accuracy: 0.3151
Epoch 9883/10000
1/1 [==============================] - 0s 102ms/step - loss: 1.5509e-06 - accuracy: 1.0000 - val_loss: 15.0764 - val_accuracy: 0.3150
Epoch 9884/10000
1/1 [==============================] - 0s 102ms/step - loss: 1.5490e-06 - accuracy: 1.0000 - val_loss: 15.0760 - val_accuracy: 0.3150
Epoch 9885/10000
1/1 [==============================] - 0s 104ms/step - loss: 1.5476e-06 - accuracy: 1.0000 - val_loss: 15.0764 - val_accuracy: 0.3151
Epoch 9886/10000
1/1 [==============================] - 0s 101ms/step - loss: 1.5459e-06 - accuracy: 1.0000 - val_loss: 15.0778 - val_accuracy: 0.3150
Epoch 9887/10000
1/1 [==============================] - 0s 107ms/step - loss: 1.5452e-06 - accuracy: 1.0000 - val_loss: 15.0790 - val_accuracy: 0.3150
Epoch 9888/10000
1/1 [==============================] - 0s 103ms/step - loss: 1.5449e-06 - accuracy: 1.0000 - val_loss: 15.0790 - val_accuracy: 0.3150
Epoch 9889/10000
1/1 [==============================] - 0s 102ms/step - loss: 1.5428e-06 - accuracy: 1.0000 - val_loss: 15.0793 - val_accuracy: 0.3152
Epoch 9890/10000
1/1 [==============================] - 0s 104ms/step - loss: 1.5407e-06 - accuracy: 1.0000 - val_loss: 15.0802 - val_accuracy: 0.3150
Epoch 9891/10000
1/1 [==============================] - 0s 106ms/step - loss: 1.5421e-06 - accuracy: 1.0000 - val_loss: 15.0814 - val_accuracy: 0.3150
Epoch 9892/10000
1/1 [==============================] - 0s 102ms/step - loss: 1.5411e-06 - accuracy: 1.0000 - val_loss: 15.0812 - val_accuracy: 0.3151
Epoch 9893/10000
1/1 [==============================] - 0s 105ms/step - loss: 1.5399e-06 - accuracy: 1.0000 - val_loss: 15.0811 - val_accuracy: 0.3151
Epoch 9894/10000
1/1 [==============================] - 0s 103ms/step - loss: 1.5373e-06 - accuracy: 1.0000 - val_loss: 15.0820 - val_accuracy: 0.3150
Epoch 9895/10000
1/1 [==============================] - 0s 102ms/step - loss: 1.5373e-06 - accuracy: 1.0000 - val_loss: 15.0831 - val_accuracy: 0.3150
Epoch 9896/10000
1/1 [==============================] - 0s 101ms/step - loss: 1.5357e-06 - accuracy: 1.0000 - val_loss: 15.0832 - val_accuracy: 0.3150
Epoch 9897/10000
1/1 [==============================] - 0s 99ms/step - loss: 1.5359e-06 - accuracy: 1.0000 - val_loss: 15.0834 - val_accuracy: 0.3150
Epoch 9898/10000
1/1 [==============================] - 0s 101ms/step - loss: 1.5354e-06 - accuracy: 1.0000 - val_loss: 15.0838 - val_accuracy: 0.3151
Epoch 9899/10000
1/1 [==============================] - 0s 109ms/step - loss: 1.5342e-06 - accuracy: 1.0000 - val_loss: 15.0845 - val_accuracy: 0.3150
Epoch 9900/10000
1/1 [==============================] - 0s 104ms/step - loss: 1.5333e-06 - accuracy: 1.0000 - val_loss: 15.0854 - val_accuracy: 0.3150
Epoch 9901/10000
1/1 [==============================] - 0s 100ms/step - loss: 1.5321e-06 - accuracy: 1.0000 - val_loss: 15.0867 - val_accuracy: 0.3151
Epoch 9902/10000
1/1 [==============================] - 0s 104ms/step - loss: 1.5323e-06 - accuracy: 1.0000 - val_loss: 15.0871 - val_accuracy: 0.3150
Epoch 9903/10000
1/1 [==============================] - 0s 100ms/step - loss: 1.5302e-06 - accuracy: 1.0000 - val_loss: 15.0870 - val_accuracy: 0.3150
Epoch 9904/10000
1/1 [==============================] - 0s 103ms/step - loss: 1.5299e-06 - accuracy: 1.0000 - val_loss: 15.0872 - val_accuracy: 0.3151
Epoch 9905/10000
1/1 [==============================] - 0s 99ms/step - loss: 1.5285e-06 - accuracy: 1.0000 - val_loss: 15.0882 - val_accuracy: 0.3151
Epoch 9906/10000
1/1 [==============================] - 0s 102ms/step - loss: 1.5275e-06 - accuracy: 1.0000 - val_loss: 15.0895 - val_accuracy: 0.3150
Epoch 9907/10000
1/1 [==============================] - 0s 107ms/step - loss: 1.5264e-06 - accuracy: 1.0000 - val_loss: 15.0900 - val_accuracy: 0.3150
Epoch 9908/10000
1/1 [==============================] - 0s 99ms/step - loss: 1.5266e-06 - accuracy: 1.0000 - val_loss: 15.0904 - val_accuracy: 0.3150
Epoch 9909/10000
1/1 [==============================] - 0s 107ms/step - loss: 1.5249e-06 - accuracy: 1.0000 - val_loss: 15.0911 - val_accuracy: 0.3150
Epoch 9910/10000
1/1 [==============================] - 0s 104ms/step - loss: 1.5233e-06 - accuracy: 1.0000 - val_loss: 15.0916 - val_accuracy: 0.3150
Epoch 9911/10000
1/1 [==============================] - 0s 104ms/step - loss: 1.5235e-06 - accuracy: 1.0000 - val_loss: 15.0921 - val_accuracy: 0.3150
Epoch 9912/10000
1/1 [==============================] - 0s 100ms/step - loss: 1.5230e-06 - accuracy: 1.0000 - val_loss: 15.0924 - val_accuracy: 0.3150
Epoch 9913/10000
1/1 [==============================] - 0s 101ms/step - loss: 1.5223e-06 - accuracy: 1.0000 - val_loss: 15.0931 - val_accuracy: 0.3151
Epoch 9914/10000
1/1 [==============================] - 0s 102ms/step - loss: 1.5206e-06 - accuracy: 1.0000 - val_loss: 15.0939 - val_accuracy: 0.3151
Epoch 9915/10000
1/1 [==============================] - 0s 102ms/step - loss: 1.5194e-06 - accuracy: 1.0000 - val_loss: 15.0941 - val_accuracy: 0.3151
Epoch 9916/10000
1/1 [==============================] - 0s 99ms/step - loss: 1.5194e-06 - accuracy: 1.0000 - val_loss: 15.0946 - val_accuracy: 0.3150
Epoch 9917/10000
1/1 [==============================] - 0s 106ms/step - loss: 1.5187e-06 - accuracy: 1.0000 - val_loss: 15.0955 - val_accuracy: 0.3150
Epoch 9918/10000
1/1 [==============================] - 0s 99ms/step - loss: 1.5173e-06 - accuracy: 1.0000 - val_loss: 15.0965 - val_accuracy: 0.3151
Epoch 9919/10000
1/1 [==============================] - 0s 102ms/step - loss: 1.5154e-06 - accuracy: 1.0000 - val_loss: 15.0968 - val_accuracy: 0.3151
Epoch 9920/10000
1/1 [==============================] - 0s 102ms/step - loss: 1.5149e-06 - accuracy: 1.0000 - val_loss: 15.0964 - val_accuracy: 0.3150
Epoch 9921/10000
1/1 [==============================] - 0s 101ms/step - loss: 1.5147e-06 - accuracy: 1.0000 - val_loss: 15.0965 - val_accuracy: 0.3150
Epoch 9922/10000
1/1 [==============================] - 0s 99ms/step - loss: 1.5156e-06 - accuracy: 1.0000 - val_loss: 15.0967 - val_accuracy: 0.3150
Epoch 9923/10000
1/1 [==============================] - 0s 101ms/step - loss: 1.5135e-06 - accuracy: 1.0000 - val_loss: 15.0979 - val_accuracy: 0.3151
Epoch 9924/10000
1/1 [==============================] - 0s 102ms/step - loss: 1.5109e-06 - accuracy: 1.0000 - val_loss: 15.0993 - val_accuracy: 0.3151
Epoch 9925/10000
1/1 [==============================] - 0s 99ms/step - loss: 1.5092e-06 - accuracy: 1.0000 - val_loss: 15.1004 - val_accuracy: 0.3151
Epoch 9926/10000
1/1 [==============================] - 0s 99ms/step - loss: 1.5109e-06 - accuracy: 1.0000 - val_loss: 15.1006 - val_accuracy: 0.3150
Epoch 9927/10000
1/1 [==============================] - 0s 107ms/step - loss: 1.5080e-06 - accuracy: 1.0000 - val_loss: 15.1011 - val_accuracy: 0.3150
Epoch 9928/10000
1/1 [==============================] - 0s 104ms/step - loss: 1.5073e-06 - accuracy: 1.0000 - val_loss: 15.1017 - val_accuracy: 0.3150
Epoch 9929/10000
1/1 [==============================] - 0s 100ms/step - loss: 1.5056e-06 - accuracy: 1.0000 - val_loss: 15.1023 - val_accuracy: 0.3150
Epoch 9930/10000
1/1 [==============================] - 0s 100ms/step - loss: 1.5061e-06 - accuracy: 1.0000 - val_loss: 15.1024 - val_accuracy: 0.3150
Epoch 9931/10000
1/1 [==============================] - 0s 101ms/step - loss: 1.5044e-06 - accuracy: 1.0000 - val_loss: 15.1026 - val_accuracy: 0.3150
Epoch 9932/10000
1/1 [==============================] - 0s 104ms/step - loss: 1.5049e-06 - accuracy: 1.0000 - val_loss: 15.1033 - val_accuracy: 0.3151
Epoch 9933/10000
1/1 [==============================] - 0s 101ms/step - loss: 1.5023e-06 - accuracy: 1.0000 - val_loss: 15.1044 - val_accuracy: 0.3151
Epoch 9934/10000
1/1 [==============================] - 0s 102ms/step - loss: 1.5008e-06 - accuracy: 1.0000 - val_loss: 15.1056 - val_accuracy: 0.3151
Epoch 9935/10000
1/1 [==============================] - 0s 108ms/step - loss: 1.4994e-06 - accuracy: 1.0000 - val_loss: 15.1061 - val_accuracy: 0.3151
Epoch 9936/10000
1/1 [==============================] - 0s 99ms/step - loss: 1.5004e-06 - accuracy: 1.0000 - val_loss: 15.1059 - val_accuracy: 0.3150
Epoch 9937/10000
1/1 [==============================] - 0s 103ms/step - loss: 1.4992e-06 - accuracy: 1.0000 - val_loss: 15.1059 - val_accuracy: 0.3151
Epoch 9938/10000
1/1 [==============================] - 0s 100ms/step - loss: 1.4989e-06 - accuracy: 1.0000 - val_loss: 15.1067 - val_accuracy: 0.3151
Epoch 9939/10000
1/1 [==============================] - 0s 99ms/step - loss: 1.4977e-06 - accuracy: 1.0000 - val_loss: 15.1080 - val_accuracy: 0.3151
Epoch 9940/10000
1/1 [==============================] - 0s 102ms/step - loss: 1.4975e-06 - accuracy: 1.0000 - val_loss: 15.1091 - val_accuracy: 0.3150
Epoch 9941/10000
1/1 [==============================] - 0s 104ms/step - loss: 1.4968e-06 - accuracy: 1.0000 - val_loss: 15.1091 - val_accuracy: 0.3150
Epoch 9942/10000
1/1 [==============================] - 0s 103ms/step - loss: 1.4961e-06 - accuracy: 1.0000 - val_loss: 15.1089 - val_accuracy: 0.3151
Epoch 9943/10000
1/1 [==============================] - 0s 102ms/step - loss: 1.4939e-06 - accuracy: 1.0000 - val_loss: 15.1096 - val_accuracy: 0.3151
Epoch 9944/10000
1/1 [==============================] - 0s 106ms/step - loss: 1.4935e-06 - accuracy: 1.0000 - val_loss: 15.1109 - val_accuracy: 0.3151
Epoch 9945/10000
1/1 [==============================] - 0s 109ms/step - loss: 1.4932e-06 - accuracy: 1.0000 - val_loss: 15.1120 - val_accuracy: 0.3151
Epoch 9946/10000
1/1 [==============================] - 0s 107ms/step - loss: 1.4935e-06 - accuracy: 1.0000 - val_loss: 15.1122 - val_accuracy: 0.3151
Epoch 9947/10000
1/1 [==============================] - 0s 112ms/step - loss: 1.4911e-06 - accuracy: 1.0000 - val_loss: 15.1119 - val_accuracy: 0.3151
Epoch 9948/10000
1/1 [==============================] - 0s 110ms/step - loss: 1.4913e-06 - accuracy: 1.0000 - val_loss: 15.1122 - val_accuracy: 0.3151
Epoch 9949/10000
1/1 [==============================] - 0s 110ms/step - loss: 1.4906e-06 - accuracy: 1.0000 - val_loss: 15.1126 - val_accuracy: 0.3151
Epoch 9950/10000
1/1 [==============================] - 0s 107ms/step - loss: 1.4892e-06 - accuracy: 1.0000 - val_loss: 15.1128 - val_accuracy: 0.3151
Epoch 9951/10000
1/1 [==============================] - 0s 107ms/step - loss: 1.4887e-06 - accuracy: 1.0000 - val_loss: 15.1137 - val_accuracy: 0.3151
Epoch 9952/10000
1/1 [==============================] - 0s 104ms/step - loss: 1.4868e-06 - accuracy: 1.0000 - val_loss: 15.1154 - val_accuracy: 0.3151
Epoch 9953/10000
1/1 [==============================] - 0s 103ms/step - loss: 1.4873e-06 - accuracy: 1.0000 - val_loss: 15.1165 - val_accuracy: 0.3151
Epoch 9954/10000
1/1 [==============================] - 0s 105ms/step - loss: 1.4863e-06 - accuracy: 1.0000 - val_loss: 15.1169 - val_accuracy: 0.3150
Epoch 9955/10000
1/1 [==============================] - 0s 100ms/step - loss: 1.4858e-06 - accuracy: 1.0000 - val_loss: 15.1169 - val_accuracy: 0.3151
Epoch 9956/10000
1/1 [==============================] - 0s 105ms/step - loss: 1.4851e-06 - accuracy: 1.0000 - val_loss: 15.1171 - val_accuracy: 0.3151
Epoch 9957/10000
1/1 [==============================] - 0s 105ms/step - loss: 1.4839e-06 - accuracy: 1.0000 - val_loss: 15.1178 - val_accuracy: 0.3150
Epoch 9958/10000
1/1 [==============================] - 0s 103ms/step - loss: 1.4842e-06 - accuracy: 1.0000 - val_loss: 15.1187 - val_accuracy: 0.3151
Epoch 9959/10000
1/1 [==============================] - 0s 100ms/step - loss: 1.4832e-06 - accuracy: 1.0000 - val_loss: 15.1192 - val_accuracy: 0.3150
Epoch 9960/10000
1/1 [==============================] - 0s 103ms/step - loss: 1.4818e-06 - accuracy: 1.0000 - val_loss: 15.1200 - val_accuracy: 0.3151
Epoch 9961/10000
1/1 [==============================] - 0s 103ms/step - loss: 1.4794e-06 - accuracy: 1.0000 - val_loss: 15.1202 - val_accuracy: 0.3151
Epoch 9962/10000
1/1 [==============================] - 0s 113ms/step - loss: 1.4796e-06 - accuracy: 1.0000 - val_loss: 15.1204 - val_accuracy: 0.3151
Epoch 9963/10000
1/1 [==============================] - 0s 105ms/step - loss: 1.4789e-06 - accuracy: 1.0000 - val_loss: 15.1212 - val_accuracy: 0.3151
Epoch 9964/10000
1/1 [==============================] - 0s 109ms/step - loss: 1.4803e-06 - accuracy: 1.0000 - val_loss: 15.1225 - val_accuracy: 0.3150
Epoch 9965/10000
1/1 [==============================] - 0s 103ms/step - loss: 1.4760e-06 - accuracy: 1.0000 - val_loss: 15.1231 - val_accuracy: 0.3150
Epoch 9966/10000
1/1 [==============================] - 0s 101ms/step - loss: 1.4739e-06 - accuracy: 1.0000 - val_loss: 15.1232 - val_accuracy: 0.3151
Epoch 9967/10000
1/1 [==============================] - 0s 105ms/step - loss: 1.4749e-06 - accuracy: 1.0000 - val_loss: 15.1233 - val_accuracy: 0.3151
Epoch 9968/10000
1/1 [==============================] - 0s 101ms/step - loss: 1.4749e-06 - accuracy: 1.0000 - val_loss: 15.1238 - val_accuracy: 0.3150
Epoch 9969/10000
1/1 [==============================] - 0s 101ms/step - loss: 1.4734e-06 - accuracy: 1.0000 - val_loss: 15.1252 - val_accuracy: 0.3150
Epoch 9970/10000
1/1 [==============================] - 0s 102ms/step - loss: 1.4725e-06 - accuracy: 1.0000 - val_loss: 15.1259 - val_accuracy: 0.3150
Epoch 9971/10000
1/1 [==============================] - 0s 100ms/step - loss: 1.4703e-06 - accuracy: 1.0000 - val_loss: 15.1256 - val_accuracy: 0.3151
Epoch 9972/10000
1/1 [==============================] - 0s 104ms/step - loss: 1.4715e-06 - accuracy: 1.0000 - val_loss: 15.1260 - val_accuracy: 0.3152
Epoch 9973/10000
1/1 [==============================] - 0s 109ms/step - loss: 1.4694e-06 - accuracy: 1.0000 - val_loss: 15.1265 - val_accuracy: 0.3150
Epoch 9974/10000
1/1 [==============================] - 0s 101ms/step - loss: 1.4677e-06 - accuracy: 1.0000 - val_loss: 15.1269 - val_accuracy: 0.3149
Epoch 9975/10000
1/1 [==============================] - 0s 103ms/step - loss: 1.4672e-06 - accuracy: 1.0000 - val_loss: 15.1277 - val_accuracy: 0.3150
Epoch 9976/10000
1/1 [==============================] - 0s 99ms/step - loss: 1.4672e-06 - accuracy: 1.0000 - val_loss: 15.1290 - val_accuracy: 0.3151
Epoch 9977/10000
1/1 [==============================] - 0s 104ms/step - loss: 1.4663e-06 - accuracy: 1.0000 - val_loss: 15.1295 - val_accuracy: 0.3151
Epoch 9978/10000
1/1 [==============================] - 0s 102ms/step - loss: 1.4646e-06 - accuracy: 1.0000 - val_loss: 15.1303 - val_accuracy: 0.3150
Epoch 9979/10000
1/1 [==============================] - 0s 102ms/step - loss: 1.4629e-06 - accuracy: 1.0000 - val_loss: 15.1303 - val_accuracy: 0.3152
Epoch 9980/10000
1/1 [==============================] - 0s 100ms/step - loss: 1.4632e-06 - accuracy: 1.0000 - val_loss: 15.1308 - val_accuracy: 0.3151
Epoch 9981/10000
1/1 [==============================] - 0s 102ms/step - loss: 1.4622e-06 - accuracy: 1.0000 - val_loss: 15.1315 - val_accuracy: 0.3151
Epoch 9982/10000
1/1 [==============================] - 0s 102ms/step - loss: 1.4598e-06 - accuracy: 1.0000 - val_loss: 15.1324 - val_accuracy: 0.3151
Epoch 9983/10000
1/1 [==============================] - 0s 101ms/step - loss: 1.4584e-06 - accuracy: 1.0000 - val_loss: 15.1329 - val_accuracy: 0.3150
Epoch 9984/10000
1/1 [==============================] - 0s 103ms/step - loss: 1.4598e-06 - accuracy: 1.0000 - val_loss: 15.1333 - val_accuracy: 0.3151
Epoch 9985/10000
1/1 [==============================] - 0s 105ms/step - loss: 1.4584e-06 - accuracy: 1.0000 - val_loss: 15.1338 - val_accuracy: 0.3151
Epoch 9986/10000
1/1 [==============================] - 0s 106ms/step - loss: 1.4563e-06 - accuracy: 1.0000 - val_loss: 15.1344 - val_accuracy: 0.3151
Epoch 9987/10000
1/1 [==============================] - 0s 104ms/step - loss: 1.4558e-06 - accuracy: 1.0000 - val_loss: 15.1350 - val_accuracy: 0.3152
Epoch 9988/10000
1/1 [==============================] - 0s 108ms/step - loss: 1.4544e-06 - accuracy: 1.0000 - val_loss: 15.1360 - val_accuracy: 0.3151
Epoch 9989/10000
1/1 [==============================] - 0s 101ms/step - loss: 1.4529e-06 - accuracy: 1.0000 - val_loss: 15.1368 - val_accuracy: 0.3152
Epoch 9990/10000
1/1 [==============================] - 0s 99ms/step - loss: 1.4524e-06 - accuracy: 1.0000 - val_loss: 15.1370 - val_accuracy: 0.3152
Epoch 9991/10000
1/1 [==============================] - 0s 101ms/step - loss: 1.4508e-06 - accuracy: 1.0000 - val_loss: 15.1373 - val_accuracy: 0.3151
Epoch 9992/10000
1/1 [==============================] - 0s 100ms/step - loss: 1.4508e-06 - accuracy: 1.0000 - val_loss: 15.1380 - val_accuracy: 0.3151
Epoch 9993/10000
1/1 [==============================] - 0s 103ms/step - loss: 1.4513e-06 - accuracy: 1.0000 - val_loss: 15.1386 - val_accuracy: 0.3151
Epoch 9994/10000
1/1 [==============================] - 0s 104ms/step - loss: 1.4489e-06 - accuracy: 1.0000 - val_loss: 15.1384 - val_accuracy: 0.3151
Epoch 9995/10000
1/1 [==============================] - 0s 103ms/step - loss: 1.4496e-06 - accuracy: 1.0000 - val_loss: 15.1383 - val_accuracy: 0.3150
Epoch 9996/10000
1/1 [==============================] - 0s 104ms/step - loss: 1.4484e-06 - accuracy: 1.0000 - val_loss: 15.1388 - val_accuracy: 0.3151
Epoch 9997/10000
1/1 [==============================] - 0s 102ms/step - loss: 1.4472e-06 - accuracy: 1.0000 - val_loss: 15.1397 - val_accuracy: 0.3151
Epoch 9998/10000
1/1 [==============================] - 0s 101ms/step - loss: 1.4465e-06 - accuracy: 1.0000 - val_loss: 15.1406 - val_accuracy: 0.3150
Epoch 9999/10000
1/1 [==============================] - 0s 102ms/step - loss: 1.4458e-06 - accuracy: 1.0000 - val_loss: 15.1415 - val_accuracy: 0.3150
Epoch 10000/10000
1/1 [==============================] - 0s 100ms/step - loss: 1.4458e-06 - accuracy: 1.0000 - val_loss: 15.1430 - val_accuracy: 0.3151
In [ ]:
#write accuracies in a csv file
import pandas as pd
data = {'Epoch': list(range(1, len(history_baseline.history['val_accuracy']) + 1)),
        'Train Accuracy': history_baseline.history['accuracy'],
        'Test Accuracy': history_baseline.history['val_accuracy']}
df = pd.DataFrame(data)

folder = '/content/gdrive/MyDrive/DLS/HW2/'
#folder = "/kaggle/working/"
csv_filename = 'baseline-q4.csv'
df.to_csv(folder + csv_filename, index=False)

The model overfits at around 400-500 epoch as the training loss from there on is a constant and is a very small values and the training accuracy is around 100 %.

c. Transfer Learning

In [ ]:
#load weights from pretext model
from keras.models import load_model
pretext_model = load_model('/content/gdrive/MyDrive/DLS/HW2/pretext.h5')
In [ ]:
#remove the last layer of the model
pretext_features = pretext_model.layers[:-1]
In [ ]:
model = Sequential()
for layer in pretext_features:
    weights = layer.get_weights()
    model.add(layer)
    model.layers[-1].set_weights(weights)

model.add(Dense(10, activation = "softmax", kernel_initializer = "he_normal"))
model.summary()

Model: "sequential_4"
_________________________________________________________________
 Layer (type)                Output Shape              Param #   
=================================================================
 conv2d (Conv2D)             (None, 32, 32, 10)        760       
                                                                 
 max_pooling2d (MaxPooling2  (None, 16, 16, 10)        0         
 D)                                                              
                                                                 
 conv2d_1 (Conv2D)           (None, 16, 16, 10)        2510      
                                                                 
 max_pooling2d_1 (MaxPoolin  (None, 8, 8, 10)          0         
 g2D)                                                            
                                                                 
 flatten_1 (Flatten)         (None, 640)               0         
                                                                 
 dense_4 (Dense)             (None, 20)                12820     
                                                                 
 dense_8 (Dense)             (None, 10)                210       
                                                                 
=================================================================
Total params: 16300 (63.67 KB)
Trainable params: 16300 (63.67 KB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
In [ ]:
#last layer learning rate = 1e-3
#rest layers = 1e-5 /1e-6
#optimizers
opt1 = tf.keras.optimizers.Adam(learning_rate = 1e-5)
opt2 = tf.keras.optimizers.Adam(learning_rate = 1e-3)

optimizers = [opt1 , opt2]
In [ ]:
#associate layers to it
optimizers_and_layers = [(optimizers[0], model.layers[:-1]), (optimizers[1], model.layers[-1])]
In [ ]:
!pip install tensorflow-addons

Collecting tensorflow-addons
  Downloading tensorflow_addons-0.22.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (612 kB)
     ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 612.3/612.3 kB 8.8 MB/s eta 0:00:00
Requirement already satisfied: packaging in /usr/local/lib/python3.10/dist-packages (from tensorflow-addons) (23.2)
Collecting typeguard<3.0.0,>=2.7 (from tensorflow-addons)
  Downloading typeguard-2.13.3-py3-none-any.whl (17 kB)
Installing collected packages: typeguard, tensorflow-addons
Successfully installed tensorflow-addons-0.22.0 typeguard-2.13.3
In [ ]:
import tensorflow_addons as tfa
optimizer = tfa.optimizers.MultiOptimizer(optimizers_and_layers)

/usr/local/lib/python3.10/dist-packages/tensorflow_addons/utils/tfa_eol_msg.py:23: UserWarning: 

TensorFlow Addons (TFA) has ended development and introduction of new features.
TFA has entered a minimal maintenance and release mode until a planned end of life in May 2024.
Please modify downstream libraries to take dependencies from other repositories in our TensorFlow community (e.g. Keras, Keras-CV, and Keras-NLP). 

For more information see: https://github.com/tensorflow/addons/issues/2807 

  warnings.warn(
  • for softmax batch size = 500 xavier initialisation val acc 28%
  • for softmax batch size = 500 default init 28%
  • softmax he normal batch size = 32 30 till 1000 epoch
  • sparse categorical he normal batch size = 500
In [ ]:
model.compile( optimizer = optimizer, loss = "sparse_categorical_crossentropy" , metrics = ["accuracy"] )
history_tf = model.fit(x_train1, y_train1 , epochs = 10000, batch_size = 500, validation_data = (x_val, y_test))

Streaming output truncated to the last 5000 lines.
1/1 [==============================] - 0s 107ms/step - loss: 0.0236 - accuracy: 1.0000 - val_loss: 7.0265 - val_accuracy: 0.3416
Epoch 7502/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0236 - accuracy: 1.0000 - val_loss: 7.0277 - val_accuracy: 0.3417
Epoch 7503/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0236 - accuracy: 1.0000 - val_loss: 7.0288 - val_accuracy: 0.3418
Epoch 7504/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0235 - accuracy: 1.0000 - val_loss: 7.0296 - val_accuracy: 0.3415
Epoch 7505/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0235 - accuracy: 1.0000 - val_loss: 7.0305 - val_accuracy: 0.3417
Epoch 7506/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0235 - accuracy: 1.0000 - val_loss: 7.0319 - val_accuracy: 0.3413
Epoch 7507/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0234 - accuracy: 1.0000 - val_loss: 7.0333 - val_accuracy: 0.3417
Epoch 7508/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0234 - accuracy: 1.0000 - val_loss: 7.0343 - val_accuracy: 0.3414
Epoch 7509/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0234 - accuracy: 1.0000 - val_loss: 7.0354 - val_accuracy: 0.3417
Epoch 7510/10000
1/1 [==============================] - 0s 104ms/step - loss: 0.0234 - accuracy: 1.0000 - val_loss: 7.0363 - val_accuracy: 0.3416
Epoch 7511/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0233 - accuracy: 1.0000 - val_loss: 7.0375 - val_accuracy: 0.3415
Epoch 7512/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0233 - accuracy: 1.0000 - val_loss: 7.0389 - val_accuracy: 0.3414
Epoch 7513/10000
1/1 [==============================] - 0s 118ms/step - loss: 0.0233 - accuracy: 1.0000 - val_loss: 7.0402 - val_accuracy: 0.3415
Epoch 7514/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0233 - accuracy: 1.0000 - val_loss: 7.0414 - val_accuracy: 0.3416
Epoch 7515/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0232 - accuracy: 1.0000 - val_loss: 7.0423 - val_accuracy: 0.3416
Epoch 7516/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0232 - accuracy: 1.0000 - val_loss: 7.0429 - val_accuracy: 0.3415
Epoch 7517/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0232 - accuracy: 1.0000 - val_loss: 7.0439 - val_accuracy: 0.3416
Epoch 7518/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0232 - accuracy: 1.0000 - val_loss: 7.0451 - val_accuracy: 0.3415
Epoch 7519/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0231 - accuracy: 1.0000 - val_loss: 7.0465 - val_accuracy: 0.3416
Epoch 7520/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0231 - accuracy: 1.0000 - val_loss: 7.0478 - val_accuracy: 0.3417
Epoch 7521/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0231 - accuracy: 1.0000 - val_loss: 7.0492 - val_accuracy: 0.3415
Epoch 7522/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0230 - accuracy: 1.0000 - val_loss: 7.0503 - val_accuracy: 0.3416
Epoch 7523/10000
1/1 [==============================] - 0s 104ms/step - loss: 0.0230 - accuracy: 1.0000 - val_loss: 7.0512 - val_accuracy: 0.3416
Epoch 7524/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0230 - accuracy: 1.0000 - val_loss: 7.0523 - val_accuracy: 0.3416
Epoch 7525/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0230 - accuracy: 1.0000 - val_loss: 7.0534 - val_accuracy: 0.3415
Epoch 7526/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0229 - accuracy: 1.0000 - val_loss: 7.0546 - val_accuracy: 0.3416
Epoch 7527/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0229 - accuracy: 1.0000 - val_loss: 7.0557 - val_accuracy: 0.3414
Epoch 7528/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0229 - accuracy: 1.0000 - val_loss: 7.0564 - val_accuracy: 0.3415
Epoch 7529/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0229 - accuracy: 1.0000 - val_loss: 7.0574 - val_accuracy: 0.3416
Epoch 7530/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0228 - accuracy: 1.0000 - val_loss: 7.0585 - val_accuracy: 0.3415
Epoch 7531/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0228 - accuracy: 1.0000 - val_loss: 7.0597 - val_accuracy: 0.3414
Epoch 7532/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0228 - accuracy: 1.0000 - val_loss: 7.0611 - val_accuracy: 0.3413
Epoch 7533/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0227 - accuracy: 1.0000 - val_loss: 7.0623 - val_accuracy: 0.3414
Epoch 7534/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0227 - accuracy: 1.0000 - val_loss: 7.0632 - val_accuracy: 0.3414
Epoch 7535/10000
1/1 [==============================] - 0s 118ms/step - loss: 0.0227 - accuracy: 1.0000 - val_loss: 7.0643 - val_accuracy: 0.3414
Epoch 7536/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0227 - accuracy: 1.0000 - val_loss: 7.0653 - val_accuracy: 0.3414
Epoch 7537/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0226 - accuracy: 1.0000 - val_loss: 7.0665 - val_accuracy: 0.3415
Epoch 7538/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0226 - accuracy: 1.0000 - val_loss: 7.0677 - val_accuracy: 0.3416
Epoch 7539/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0226 - accuracy: 1.0000 - val_loss: 7.0686 - val_accuracy: 0.3415
Epoch 7540/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0226 - accuracy: 1.0000 - val_loss: 7.0697 - val_accuracy: 0.3416
Epoch 7541/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0225 - accuracy: 1.0000 - val_loss: 7.0710 - val_accuracy: 0.3417
Epoch 7542/10000
1/1 [==============================] - 0s 117ms/step - loss: 0.0225 - accuracy: 1.0000 - val_loss: 7.0720 - val_accuracy: 0.3417
Epoch 7543/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0225 - accuracy: 1.0000 - val_loss: 7.0732 - val_accuracy: 0.3416
Epoch 7544/10000
1/1 [==============================] - 0s 118ms/step - loss: 0.0225 - accuracy: 1.0000 - val_loss: 7.0742 - val_accuracy: 0.3416
Epoch 7545/10000
1/1 [==============================] - 0s 120ms/step - loss: 0.0224 - accuracy: 1.0000 - val_loss: 7.0755 - val_accuracy: 0.3416
Epoch 7546/10000
1/1 [==============================] - 0s 121ms/step - loss: 0.0224 - accuracy: 1.0000 - val_loss: 7.0765 - val_accuracy: 0.3416
Epoch 7547/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0224 - accuracy: 1.0000 - val_loss: 7.0774 - val_accuracy: 0.3415
Epoch 7548/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0224 - accuracy: 1.0000 - val_loss: 7.0785 - val_accuracy: 0.3414
Epoch 7549/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0223 - accuracy: 1.0000 - val_loss: 7.0797 - val_accuracy: 0.3418
Epoch 7550/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0223 - accuracy: 1.0000 - val_loss: 7.0809 - val_accuracy: 0.3416
Epoch 7551/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0223 - accuracy: 1.0000 - val_loss: 7.0820 - val_accuracy: 0.3417
Epoch 7552/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0223 - accuracy: 1.0000 - val_loss: 7.0828 - val_accuracy: 0.3415
Epoch 7553/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0222 - accuracy: 1.0000 - val_loss: 7.0837 - val_accuracy: 0.3417
Epoch 7554/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0222 - accuracy: 1.0000 - val_loss: 7.0850 - val_accuracy: 0.3418
Epoch 7555/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0222 - accuracy: 1.0000 - val_loss: 7.0864 - val_accuracy: 0.3415
Epoch 7556/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0222 - accuracy: 1.0000 - val_loss: 7.0878 - val_accuracy: 0.3418
Epoch 7557/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0221 - accuracy: 1.0000 - val_loss: 7.0888 - val_accuracy: 0.3417
Epoch 7558/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0221 - accuracy: 1.0000 - val_loss: 7.0897 - val_accuracy: 0.3417
Epoch 7559/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0221 - accuracy: 1.0000 - val_loss: 7.0907 - val_accuracy: 0.3418
Epoch 7560/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0220 - accuracy: 1.0000 - val_loss: 7.0917 - val_accuracy: 0.3418
Epoch 7561/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0220 - accuracy: 1.0000 - val_loss: 7.0927 - val_accuracy: 0.3418
Epoch 7562/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0220 - accuracy: 1.0000 - val_loss: 7.0939 - val_accuracy: 0.3418
Epoch 7563/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0220 - accuracy: 1.0000 - val_loss: 7.0948 - val_accuracy: 0.3419
Epoch 7564/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0220 - accuracy: 1.0000 - val_loss: 7.0957 - val_accuracy: 0.3418
Epoch 7565/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0219 - accuracy: 1.0000 - val_loss: 7.0969 - val_accuracy: 0.3419
Epoch 7566/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0219 - accuracy: 1.0000 - val_loss: 7.0979 - val_accuracy: 0.3419
Epoch 7567/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0219 - accuracy: 1.0000 - val_loss: 7.0990 - val_accuracy: 0.3420
Epoch 7568/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0219 - accuracy: 1.0000 - val_loss: 7.1002 - val_accuracy: 0.3418
Epoch 7569/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0218 - accuracy: 1.0000 - val_loss: 7.1013 - val_accuracy: 0.3419
Epoch 7570/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0218 - accuracy: 1.0000 - val_loss: 7.1025 - val_accuracy: 0.3419
Epoch 7571/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0218 - accuracy: 1.0000 - val_loss: 7.1038 - val_accuracy: 0.3418
Epoch 7572/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0218 - accuracy: 1.0000 - val_loss: 7.1050 - val_accuracy: 0.3419
Epoch 7573/10000
1/1 [==============================] - 0s 102ms/step - loss: 0.0217 - accuracy: 1.0000 - val_loss: 7.1061 - val_accuracy: 0.3420
Epoch 7574/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0217 - accuracy: 1.0000 - val_loss: 7.1072 - val_accuracy: 0.3418
Epoch 7575/10000
1/1 [==============================] - 0s 102ms/step - loss: 0.0217 - accuracy: 1.0000 - val_loss: 7.1083 - val_accuracy: 0.3416
Epoch 7576/10000
1/1 [==============================] - 0s 104ms/step - loss: 0.0217 - accuracy: 1.0000 - val_loss: 7.1094 - val_accuracy: 0.3417
Epoch 7577/10000
1/1 [==============================] - 0s 102ms/step - loss: 0.0216 - accuracy: 1.0000 - val_loss: 7.1105 - val_accuracy: 0.3416
Epoch 7578/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0216 - accuracy: 1.0000 - val_loss: 7.1118 - val_accuracy: 0.3420
Epoch 7579/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0216 - accuracy: 1.0000 - val_loss: 7.1126 - val_accuracy: 0.3419
Epoch 7580/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0216 - accuracy: 1.0000 - val_loss: 7.1135 - val_accuracy: 0.3418
Epoch 7581/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0215 - accuracy: 1.0000 - val_loss: 7.1146 - val_accuracy: 0.3417
Epoch 7582/10000
1/1 [==============================] - 0s 104ms/step - loss: 0.0215 - accuracy: 1.0000 - val_loss: 7.1160 - val_accuracy: 0.3418
Epoch 7583/10000
1/1 [==============================] - 0s 116ms/step - loss: 0.0215 - accuracy: 1.0000 - val_loss: 7.1172 - val_accuracy: 0.3419
Epoch 7584/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0215 - accuracy: 1.0000 - val_loss: 7.1181 - val_accuracy: 0.3419
Epoch 7585/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0214 - accuracy: 1.0000 - val_loss: 7.1188 - val_accuracy: 0.3418
Epoch 7586/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0214 - accuracy: 1.0000 - val_loss: 7.1197 - val_accuracy: 0.3418
Epoch 7587/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0214 - accuracy: 1.0000 - val_loss: 7.1208 - val_accuracy: 0.3418
Epoch 7588/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0214 - accuracy: 1.0000 - val_loss: 7.1221 - val_accuracy: 0.3420
Epoch 7589/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0213 - accuracy: 1.0000 - val_loss: 7.1235 - val_accuracy: 0.3420
Epoch 7590/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0213 - accuracy: 1.0000 - val_loss: 7.1248 - val_accuracy: 0.3419
Epoch 7591/10000
1/1 [==============================] - 0s 102ms/step - loss: 0.0213 - accuracy: 1.0000 - val_loss: 7.1255 - val_accuracy: 0.3420
Epoch 7592/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0213 - accuracy: 1.0000 - val_loss: 7.1264 - val_accuracy: 0.3419
Epoch 7593/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0212 - accuracy: 1.0000 - val_loss: 7.1275 - val_accuracy: 0.3419
Epoch 7594/10000
1/1 [==============================] - 0s 104ms/step - loss: 0.0212 - accuracy: 1.0000 - val_loss: 7.1288 - val_accuracy: 0.3419
Epoch 7595/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0212 - accuracy: 1.0000 - val_loss: 7.1302 - val_accuracy: 0.3420
Epoch 7596/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0212 - accuracy: 1.0000 - val_loss: 7.1313 - val_accuracy: 0.3419
Epoch 7597/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0211 - accuracy: 1.0000 - val_loss: 7.1321 - val_accuracy: 0.3419
Epoch 7598/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0211 - accuracy: 1.0000 - val_loss: 7.1328 - val_accuracy: 0.3419
Epoch 7599/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0211 - accuracy: 1.0000 - val_loss: 7.1337 - val_accuracy: 0.3419
Epoch 7600/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0211 - accuracy: 1.0000 - val_loss: 7.1349 - val_accuracy: 0.3420
Epoch 7601/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0210 - accuracy: 1.0000 - val_loss: 7.1362 - val_accuracy: 0.3418
Epoch 7602/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0210 - accuracy: 1.0000 - val_loss: 7.1373 - val_accuracy: 0.3419
Epoch 7603/10000
1/1 [==============================] - 0s 103ms/step - loss: 0.0210 - accuracy: 1.0000 - val_loss: 7.1384 - val_accuracy: 0.3420
Epoch 7604/10000
1/1 [==============================] - 0s 104ms/step - loss: 0.0210 - accuracy: 1.0000 - val_loss: 7.1393 - val_accuracy: 0.3420
Epoch 7605/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0210 - accuracy: 1.0000 - val_loss: 7.1405 - val_accuracy: 0.3421
Epoch 7606/10000
1/1 [==============================] - 0s 104ms/step - loss: 0.0209 - accuracy: 1.0000 - val_loss: 7.1417 - val_accuracy: 0.3419
Epoch 7607/10000
1/1 [==============================] - 0s 102ms/step - loss: 0.0209 - accuracy: 1.0000 - val_loss: 7.1429 - val_accuracy: 0.3420
Epoch 7608/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0209 - accuracy: 1.0000 - val_loss: 7.1440 - val_accuracy: 0.3420
Epoch 7609/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0209 - accuracy: 1.0000 - val_loss: 7.1451 - val_accuracy: 0.3420
Epoch 7610/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0208 - accuracy: 1.0000 - val_loss: 7.1462 - val_accuracy: 0.3419
Epoch 7611/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0208 - accuracy: 1.0000 - val_loss: 7.1474 - val_accuracy: 0.3419
Epoch 7612/10000
1/1 [==============================] - 0s 104ms/step - loss: 0.0208 - accuracy: 1.0000 - val_loss: 7.1481 - val_accuracy: 0.3420
Epoch 7613/10000
1/1 [==============================] - 0s 119ms/step - loss: 0.0208 - accuracy: 1.0000 - val_loss: 7.1490 - val_accuracy: 0.3419
Epoch 7614/10000
1/1 [==============================] - 0s 117ms/step - loss: 0.0207 - accuracy: 1.0000 - val_loss: 7.1501 - val_accuracy: 0.3419
Epoch 7615/10000
1/1 [==============================] - 0s 122ms/step - loss: 0.0207 - accuracy: 1.0000 - val_loss: 7.1515 - val_accuracy: 0.3418
Epoch 7616/10000
1/1 [==============================] - 0s 125ms/step - loss: 0.0207 - accuracy: 1.0000 - val_loss: 7.1525 - val_accuracy: 0.3418
Epoch 7617/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0207 - accuracy: 1.0000 - val_loss: 7.1536 - val_accuracy: 0.3418
Epoch 7618/10000
1/1 [==============================] - 0s 117ms/step - loss: 0.0206 - accuracy: 1.0000 - val_loss: 7.1545 - val_accuracy: 0.3418
Epoch 7619/10000
1/1 [==============================] - 0s 120ms/step - loss: 0.0206 - accuracy: 1.0000 - val_loss: 7.1555 - val_accuracy: 0.3418
Epoch 7620/10000
1/1 [==============================] - 0s 116ms/step - loss: 0.0206 - accuracy: 1.0000 - val_loss: 7.1567 - val_accuracy: 0.3418
Epoch 7621/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0206 - accuracy: 1.0000 - val_loss: 7.1579 - val_accuracy: 0.3419
Epoch 7622/10000
1/1 [==============================] - 0s 117ms/step - loss: 0.0205 - accuracy: 1.0000 - val_loss: 7.1592 - val_accuracy: 0.3418
Epoch 7623/10000
1/1 [==============================] - 0s 120ms/step - loss: 0.0205 - accuracy: 1.0000 - val_loss: 7.1601 - val_accuracy: 0.3419
Epoch 7624/10000
1/1 [==============================] - 0s 116ms/step - loss: 0.0205 - accuracy: 1.0000 - val_loss: 7.1611 - val_accuracy: 0.3418
Epoch 7625/10000
1/1 [==============================] - 0s 119ms/step - loss: 0.0205 - accuracy: 1.0000 - val_loss: 7.1622 - val_accuracy: 0.3417
Epoch 7626/10000
1/1 [==============================] - 0s 120ms/step - loss: 0.0205 - accuracy: 1.0000 - val_loss: 7.1634 - val_accuracy: 0.3418
Epoch 7627/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0204 - accuracy: 1.0000 - val_loss: 7.1645 - val_accuracy: 0.3419
Epoch 7628/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0204 - accuracy: 1.0000 - val_loss: 7.1656 - val_accuracy: 0.3419
Epoch 7629/10000
1/1 [==============================] - 0s 117ms/step - loss: 0.0204 - accuracy: 1.0000 - val_loss: 7.1666 - val_accuracy: 0.3419
Epoch 7630/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0204 - accuracy: 1.0000 - val_loss: 7.1673 - val_accuracy: 0.3419
Epoch 7631/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0203 - accuracy: 1.0000 - val_loss: 7.1683 - val_accuracy: 0.3418
Epoch 7632/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0203 - accuracy: 1.0000 - val_loss: 7.1695 - val_accuracy: 0.3419
Epoch 7633/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0203 - accuracy: 1.0000 - val_loss: 7.1708 - val_accuracy: 0.3417
Epoch 7634/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0203 - accuracy: 1.0000 - val_loss: 7.1721 - val_accuracy: 0.3417
Epoch 7635/10000
1/1 [==============================] - 0s 119ms/step - loss: 0.0202 - accuracy: 1.0000 - val_loss: 7.1726 - val_accuracy: 0.3418
Epoch 7636/10000
1/1 [==============================] - 0s 122ms/step - loss: 0.0202 - accuracy: 1.0000 - val_loss: 7.1733 - val_accuracy: 0.3419
Epoch 7637/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0202 - accuracy: 1.0000 - val_loss: 7.1743 - val_accuracy: 0.3418
Epoch 7638/10000
1/1 [==============================] - 0s 121ms/step - loss: 0.0202 - accuracy: 1.0000 - val_loss: 7.1755 - val_accuracy: 0.3417
Epoch 7639/10000
1/1 [==============================] - 0s 117ms/step - loss: 0.0202 - accuracy: 1.0000 - val_loss: 7.1768 - val_accuracy: 0.3418
Epoch 7640/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0201 - accuracy: 1.0000 - val_loss: 7.1781 - val_accuracy: 0.3418
Epoch 7641/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0201 - accuracy: 1.0000 - val_loss: 7.1791 - val_accuracy: 0.3418
Epoch 7642/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0201 - accuracy: 1.0000 - val_loss: 7.1802 - val_accuracy: 0.3420
Epoch 7643/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0201 - accuracy: 1.0000 - val_loss: 7.1814 - val_accuracy: 0.3418
Epoch 7644/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0200 - accuracy: 1.0000 - val_loss: 7.1826 - val_accuracy: 0.3420
Epoch 7645/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0200 - accuracy: 1.0000 - val_loss: 7.1837 - val_accuracy: 0.3419
Epoch 7646/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0200 - accuracy: 1.0000 - val_loss: 7.1847 - val_accuracy: 0.3419
Epoch 7647/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0200 - accuracy: 1.0000 - val_loss: 7.1856 - val_accuracy: 0.3419
Epoch 7648/10000
1/1 [==============================] - 0s 118ms/step - loss: 0.0200 - accuracy: 1.0000 - val_loss: 7.1866 - val_accuracy: 0.3420
Epoch 7649/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0199 - accuracy: 1.0000 - val_loss: 7.1879 - val_accuracy: 0.3419
Epoch 7650/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0199 - accuracy: 1.0000 - val_loss: 7.1891 - val_accuracy: 0.3419
Epoch 7651/10000
1/1 [==============================] - 0s 116ms/step - loss: 0.0199 - accuracy: 1.0000 - val_loss: 7.1903 - val_accuracy: 0.3416
Epoch 7652/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0199 - accuracy: 1.0000 - val_loss: 7.1911 - val_accuracy: 0.3418
Epoch 7653/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0198 - accuracy: 1.0000 - val_loss: 7.1917 - val_accuracy: 0.3420
Epoch 7654/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0198 - accuracy: 1.0000 - val_loss: 7.1927 - val_accuracy: 0.3419
Epoch 7655/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0198 - accuracy: 1.0000 - val_loss: 7.1937 - val_accuracy: 0.3420
Epoch 7656/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0198 - accuracy: 1.0000 - val_loss: 7.1950 - val_accuracy: 0.3419
Epoch 7657/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0198 - accuracy: 1.0000 - val_loss: 7.1963 - val_accuracy: 0.3418
Epoch 7658/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0197 - accuracy: 1.0000 - val_loss: 7.1976 - val_accuracy: 0.3418
Epoch 7659/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0197 - accuracy: 1.0000 - val_loss: 7.1987 - val_accuracy: 0.3419
Epoch 7660/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0197 - accuracy: 1.0000 - val_loss: 7.1997 - val_accuracy: 0.3419
Epoch 7661/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0197 - accuracy: 1.0000 - val_loss: 7.2007 - val_accuracy: 0.3419
Epoch 7662/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0196 - accuracy: 1.0000 - val_loss: 7.2015 - val_accuracy: 0.3419
Epoch 7663/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0196 - accuracy: 1.0000 - val_loss: 7.2025 - val_accuracy: 0.3419
Epoch 7664/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0196 - accuracy: 1.0000 - val_loss: 7.2035 - val_accuracy: 0.3418
Epoch 7665/10000
1/1 [==============================] - 0s 103ms/step - loss: 0.0196 - accuracy: 1.0000 - val_loss: 7.2044 - val_accuracy: 0.3416
Epoch 7666/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0196 - accuracy: 1.0000 - val_loss: 7.2053 - val_accuracy: 0.3419
Epoch 7667/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0195 - accuracy: 1.0000 - val_loss: 7.2064 - val_accuracy: 0.3420
Epoch 7668/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0195 - accuracy: 1.0000 - val_loss: 7.2076 - val_accuracy: 0.3421
Epoch 7669/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0195 - accuracy: 1.0000 - val_loss: 7.2088 - val_accuracy: 0.3421
Epoch 7670/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0195 - accuracy: 1.0000 - val_loss: 7.2101 - val_accuracy: 0.3422
Epoch 7671/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0194 - accuracy: 1.0000 - val_loss: 7.2111 - val_accuracy: 0.3420
Epoch 7672/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0194 - accuracy: 1.0000 - val_loss: 7.2117 - val_accuracy: 0.3422
Epoch 7673/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0194 - accuracy: 1.0000 - val_loss: 7.2127 - val_accuracy: 0.3422
Epoch 7674/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0194 - accuracy: 1.0000 - val_loss: 7.2138 - val_accuracy: 0.3422
Epoch 7675/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0194 - accuracy: 1.0000 - val_loss: 7.2152 - val_accuracy: 0.3422
Epoch 7676/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0193 - accuracy: 1.0000 - val_loss: 7.2165 - val_accuracy: 0.3420
Epoch 7677/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0193 - accuracy: 1.0000 - val_loss: 7.2176 - val_accuracy: 0.3421
Epoch 7678/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0193 - accuracy: 1.0000 - val_loss: 7.2184 - val_accuracy: 0.3420
Epoch 7679/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0193 - accuracy: 1.0000 - val_loss: 7.2194 - val_accuracy: 0.3421
Epoch 7680/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0193 - accuracy: 1.0000 - val_loss: 7.2205 - val_accuracy: 0.3421
Epoch 7681/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0192 - accuracy: 1.0000 - val_loss: 7.2217 - val_accuracy: 0.3423
Epoch 7682/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0192 - accuracy: 1.0000 - val_loss: 7.2225 - val_accuracy: 0.3424
Epoch 7683/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0192 - accuracy: 1.0000 - val_loss: 7.2235 - val_accuracy: 0.3423
Epoch 7684/10000
1/1 [==============================] - 0s 103ms/step - loss: 0.0192 - accuracy: 1.0000 - val_loss: 7.2244 - val_accuracy: 0.3424
Epoch 7685/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0191 - accuracy: 1.0000 - val_loss: 7.2254 - val_accuracy: 0.3424
Epoch 7686/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0191 - accuracy: 1.0000 - val_loss: 7.2265 - val_accuracy: 0.3423
Epoch 7687/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0191 - accuracy: 1.0000 - val_loss: 7.2277 - val_accuracy: 0.3424
Epoch 7688/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0191 - accuracy: 1.0000 - val_loss: 7.2288 - val_accuracy: 0.3424
Epoch 7689/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0191 - accuracy: 1.0000 - val_loss: 7.2297 - val_accuracy: 0.3424
Epoch 7690/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0190 - accuracy: 1.0000 - val_loss: 7.2307 - val_accuracy: 0.3426
Epoch 7691/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0190 - accuracy: 1.0000 - val_loss: 7.2318 - val_accuracy: 0.3425
Epoch 7692/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0190 - accuracy: 1.0000 - val_loss: 7.2330 - val_accuracy: 0.3425
Epoch 7693/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0190 - accuracy: 1.0000 - val_loss: 7.2339 - val_accuracy: 0.3425
Epoch 7694/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0190 - accuracy: 1.0000 - val_loss: 7.2348 - val_accuracy: 0.3424
Epoch 7695/10000
1/1 [==============================] - 0s 103ms/step - loss: 0.0189 - accuracy: 1.0000 - val_loss: 7.2358 - val_accuracy: 0.3425
Epoch 7696/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0189 - accuracy: 1.0000 - val_loss: 7.2370 - val_accuracy: 0.3426
Epoch 7697/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0189 - accuracy: 1.0000 - val_loss: 7.2382 - val_accuracy: 0.3425
Epoch 7698/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0189 - accuracy: 1.0000 - val_loss: 7.2392 - val_accuracy: 0.3427
Epoch 7699/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0188 - accuracy: 1.0000 - val_loss: 7.2402 - val_accuracy: 0.3424
Epoch 7700/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0188 - accuracy: 1.0000 - val_loss: 7.2413 - val_accuracy: 0.3426
Epoch 7701/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0188 - accuracy: 1.0000 - val_loss: 7.2425 - val_accuracy: 0.3425
Epoch 7702/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0188 - accuracy: 1.0000 - val_loss: 7.2434 - val_accuracy: 0.3425
Epoch 7703/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0188 - accuracy: 1.0000 - val_loss: 7.2443 - val_accuracy: 0.3427
Epoch 7704/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0187 - accuracy: 1.0000 - val_loss: 7.2453 - val_accuracy: 0.3425
Epoch 7705/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0187 - accuracy: 1.0000 - val_loss: 7.2463 - val_accuracy: 0.3426
Epoch 7706/10000
1/1 [==============================] - 0s 118ms/step - loss: 0.0187 - accuracy: 1.0000 - val_loss: 7.2475 - val_accuracy: 0.3426
Epoch 7707/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0187 - accuracy: 1.0000 - val_loss: 7.2486 - val_accuracy: 0.3427
Epoch 7708/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0187 - accuracy: 1.0000 - val_loss: 7.2496 - val_accuracy: 0.3426
Epoch 7709/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0186 - accuracy: 1.0000 - val_loss: 7.2506 - val_accuracy: 0.3428
Epoch 7710/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0186 - accuracy: 1.0000 - val_loss: 7.2517 - val_accuracy: 0.3428
Epoch 7711/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0186 - accuracy: 1.0000 - val_loss: 7.2528 - val_accuracy: 0.3425
Epoch 7712/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0186 - accuracy: 1.0000 - val_loss: 7.2537 - val_accuracy: 0.3425
Epoch 7713/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0186 - accuracy: 1.0000 - val_loss: 7.2544 - val_accuracy: 0.3426
Epoch 7714/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0185 - accuracy: 1.0000 - val_loss: 7.2553 - val_accuracy: 0.3427
Epoch 7715/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0185 - accuracy: 1.0000 - val_loss: 7.2565 - val_accuracy: 0.3428
Epoch 7716/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0185 - accuracy: 1.0000 - val_loss: 7.2579 - val_accuracy: 0.3427
Epoch 7717/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0185 - accuracy: 1.0000 - val_loss: 7.2593 - val_accuracy: 0.3428
Epoch 7718/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0185 - accuracy: 1.0000 - val_loss: 7.2604 - val_accuracy: 0.3427
Epoch 7719/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0184 - accuracy: 1.0000 - val_loss: 7.2611 - val_accuracy: 0.3427
Epoch 7720/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0184 - accuracy: 1.0000 - val_loss: 7.2618 - val_accuracy: 0.3426
Epoch 7721/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0184 - accuracy: 1.0000 - val_loss: 7.2627 - val_accuracy: 0.3427
Epoch 7722/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0184 - accuracy: 1.0000 - val_loss: 7.2638 - val_accuracy: 0.3427
Epoch 7723/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0184 - accuracy: 1.0000 - val_loss: 7.2650 - val_accuracy: 0.3427
Epoch 7724/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0183 - accuracy: 1.0000 - val_loss: 7.2662 - val_accuracy: 0.3428
Epoch 7725/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0183 - accuracy: 1.0000 - val_loss: 7.2671 - val_accuracy: 0.3428
Epoch 7726/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0183 - accuracy: 1.0000 - val_loss: 7.2679 - val_accuracy: 0.3428
Epoch 7727/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0183 - accuracy: 1.0000 - val_loss: 7.2688 - val_accuracy: 0.3428
Epoch 7728/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0183 - accuracy: 1.0000 - val_loss: 7.2698 - val_accuracy: 0.3428
Epoch 7729/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0182 - accuracy: 1.0000 - val_loss: 7.2711 - val_accuracy: 0.3429
Epoch 7730/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0182 - accuracy: 1.0000 - val_loss: 7.2724 - val_accuracy: 0.3427
Epoch 7731/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0182 - accuracy: 1.0000 - val_loss: 7.2735 - val_accuracy: 0.3427
Epoch 7732/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0182 - accuracy: 1.0000 - val_loss: 7.2744 - val_accuracy: 0.3428
Epoch 7733/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0182 - accuracy: 1.0000 - val_loss: 7.2754 - val_accuracy: 0.3427
Epoch 7734/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0181 - accuracy: 1.0000 - val_loss: 7.2764 - val_accuracy: 0.3426
Epoch 7735/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0181 - accuracy: 1.0000 - val_loss: 7.2775 - val_accuracy: 0.3427
Epoch 7736/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0181 - accuracy: 1.0000 - val_loss: 7.2789 - val_accuracy: 0.3427
Epoch 7737/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0181 - accuracy: 1.0000 - val_loss: 7.2800 - val_accuracy: 0.3428
Epoch 7738/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0181 - accuracy: 1.0000 - val_loss: 7.2809 - val_accuracy: 0.3427
Epoch 7739/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0180 - accuracy: 1.0000 - val_loss: 7.2816 - val_accuracy: 0.3428
Epoch 7740/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0180 - accuracy: 1.0000 - val_loss: 7.2824 - val_accuracy: 0.3427
Epoch 7741/10000
1/1 [==============================] - 0s 118ms/step - loss: 0.0180 - accuracy: 1.0000 - val_loss: 7.2835 - val_accuracy: 0.3427
Epoch 7742/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0180 - accuracy: 1.0000 - val_loss: 7.2847 - val_accuracy: 0.3427
Epoch 7743/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0180 - accuracy: 1.0000 - val_loss: 7.2861 - val_accuracy: 0.3427
Epoch 7744/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0179 - accuracy: 1.0000 - val_loss: 7.2872 - val_accuracy: 0.3426
Epoch 7745/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0179 - accuracy: 1.0000 - val_loss: 7.2880 - val_accuracy: 0.3428
Epoch 7746/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0179 - accuracy: 1.0000 - val_loss: 7.2886 - val_accuracy: 0.3427
Epoch 7747/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0179 - accuracy: 1.0000 - val_loss: 7.2894 - val_accuracy: 0.3426
Epoch 7748/10000
1/1 [==============================] - 0s 120ms/step - loss: 0.0179 - accuracy: 1.0000 - val_loss: 7.2903 - val_accuracy: 0.3427
Epoch 7749/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0178 - accuracy: 1.0000 - val_loss: 7.2915 - val_accuracy: 0.3425
Epoch 7750/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0178 - accuracy: 1.0000 - val_loss: 7.2928 - val_accuracy: 0.3426
Epoch 7751/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0178 - accuracy: 1.0000 - val_loss: 7.2940 - val_accuracy: 0.3425
Epoch 7752/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0178 - accuracy: 1.0000 - val_loss: 7.2950 - val_accuracy: 0.3426
Epoch 7753/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0178 - accuracy: 1.0000 - val_loss: 7.2958 - val_accuracy: 0.3427
Epoch 7754/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0177 - accuracy: 1.0000 - val_loss: 7.2969 - val_accuracy: 0.3427
Epoch 7755/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0177 - accuracy: 1.0000 - val_loss: 7.2980 - val_accuracy: 0.3426
Epoch 7756/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0177 - accuracy: 1.0000 - val_loss: 7.2993 - val_accuracy: 0.3427
Epoch 7757/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0177 - accuracy: 1.0000 - val_loss: 7.3003 - val_accuracy: 0.3426
Epoch 7758/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0177 - accuracy: 1.0000 - val_loss: 7.3013 - val_accuracy: 0.3426
Epoch 7759/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0176 - accuracy: 1.0000 - val_loss: 7.3020 - val_accuracy: 0.3427
Epoch 7760/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0176 - accuracy: 1.0000 - val_loss: 7.3030 - val_accuracy: 0.3426
Epoch 7761/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0176 - accuracy: 1.0000 - val_loss: 7.3040 - val_accuracy: 0.3425
Epoch 7762/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0176 - accuracy: 1.0000 - val_loss: 7.3051 - val_accuracy: 0.3425
Epoch 7763/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0176 - accuracy: 1.0000 - val_loss: 7.3062 - val_accuracy: 0.3426
Epoch 7764/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0175 - accuracy: 1.0000 - val_loss: 7.3071 - val_accuracy: 0.3426
Epoch 7765/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0175 - accuracy: 1.0000 - val_loss: 7.3081 - val_accuracy: 0.3426
Epoch 7766/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0175 - accuracy: 1.0000 - val_loss: 7.3093 - val_accuracy: 0.3427
Epoch 7767/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0175 - accuracy: 1.0000 - val_loss: 7.3105 - val_accuracy: 0.3427
Epoch 7768/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0175 - accuracy: 1.0000 - val_loss: 7.3115 - val_accuracy: 0.3427
Epoch 7769/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0174 - accuracy: 1.0000 - val_loss: 7.3125 - val_accuracy: 0.3426
Epoch 7770/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0174 - accuracy: 1.0000 - val_loss: 7.3132 - val_accuracy: 0.3426
Epoch 7771/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0174 - accuracy: 1.0000 - val_loss: 7.3141 - val_accuracy: 0.3426
Epoch 7772/10000
1/1 [==============================] - 0s 116ms/step - loss: 0.0174 - accuracy: 1.0000 - val_loss: 7.3151 - val_accuracy: 0.3426
Epoch 7773/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0174 - accuracy: 1.0000 - val_loss: 7.3162 - val_accuracy: 0.3426
Epoch 7774/10000
1/1 [==============================] - 0s 119ms/step - loss: 0.0174 - accuracy: 1.0000 - val_loss: 7.3174 - val_accuracy: 0.3426
Epoch 7775/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0173 - accuracy: 1.0000 - val_loss: 7.3186 - val_accuracy: 0.3426
Epoch 7776/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0173 - accuracy: 1.0000 - val_loss: 7.3197 - val_accuracy: 0.3426
Epoch 7777/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0173 - accuracy: 1.0000 - val_loss: 7.3204 - val_accuracy: 0.3426
Epoch 7778/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0173 - accuracy: 1.0000 - val_loss: 7.3212 - val_accuracy: 0.3426
Epoch 7779/10000
1/1 [==============================] - 0s 120ms/step - loss: 0.0173 - accuracy: 1.0000 - val_loss: 7.3221 - val_accuracy: 0.3426
Epoch 7780/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0172 - accuracy: 1.0000 - val_loss: 7.3233 - val_accuracy: 0.3426
Epoch 7781/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0172 - accuracy: 1.0000 - val_loss: 7.3245 - val_accuracy: 0.3426
Epoch 7782/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0172 - accuracy: 1.0000 - val_loss: 7.3252 - val_accuracy: 0.3426
Epoch 7783/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0172 - accuracy: 1.0000 - val_loss: 7.3262 - val_accuracy: 0.3426
Epoch 7784/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0172 - accuracy: 1.0000 - val_loss: 7.3274 - val_accuracy: 0.3426
Epoch 7785/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0171 - accuracy: 1.0000 - val_loss: 7.3288 - val_accuracy: 0.3426
Epoch 7786/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0171 - accuracy: 1.0000 - val_loss: 7.3299 - val_accuracy: 0.3426
Epoch 7787/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0171 - accuracy: 1.0000 - val_loss: 7.3308 - val_accuracy: 0.3426
Epoch 7788/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0171 - accuracy: 1.0000 - val_loss: 7.3318 - val_accuracy: 0.3426
Epoch 7789/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0171 - accuracy: 1.0000 - val_loss: 7.3328 - val_accuracy: 0.3426
Epoch 7790/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0171 - accuracy: 1.0000 - val_loss: 7.3337 - val_accuracy: 0.3426
Epoch 7791/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0170 - accuracy: 1.0000 - val_loss: 7.3346 - val_accuracy: 0.3426
Epoch 7792/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0170 - accuracy: 1.0000 - val_loss: 7.3354 - val_accuracy: 0.3426
Epoch 7793/10000
1/1 [==============================] - 0s 117ms/step - loss: 0.0170 - accuracy: 1.0000 - val_loss: 7.3363 - val_accuracy: 0.3426
Epoch 7794/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0170 - accuracy: 1.0000 - val_loss: 7.3374 - val_accuracy: 0.3427
Epoch 7795/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0170 - accuracy: 1.0000 - val_loss: 7.3384 - val_accuracy: 0.3427
Epoch 7796/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0169 - accuracy: 1.0000 - val_loss: 7.3396 - val_accuracy: 0.3427
Epoch 7797/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0169 - accuracy: 1.0000 - val_loss: 7.3407 - val_accuracy: 0.3426
Epoch 7798/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0169 - accuracy: 1.0000 - val_loss: 7.3414 - val_accuracy: 0.3426
Epoch 7799/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0169 - accuracy: 1.0000 - val_loss: 7.3422 - val_accuracy: 0.3426
Epoch 7800/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0169 - accuracy: 1.0000 - val_loss: 7.3432 - val_accuracy: 0.3426
Epoch 7801/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0169 - accuracy: 1.0000 - val_loss: 7.3443 - val_accuracy: 0.3426
Epoch 7802/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0168 - accuracy: 1.0000 - val_loss: 7.3456 - val_accuracy: 0.3428
Epoch 7803/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0168 - accuracy: 1.0000 - val_loss: 7.3469 - val_accuracy: 0.3429
Epoch 7804/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0168 - accuracy: 1.0000 - val_loss: 7.3480 - val_accuracy: 0.3428
Epoch 7805/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0168 - accuracy: 1.0000 - val_loss: 7.3489 - val_accuracy: 0.3427
Epoch 7806/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0168 - accuracy: 1.0000 - val_loss: 7.3495 - val_accuracy: 0.3426
Epoch 7807/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0167 - accuracy: 1.0000 - val_loss: 7.3502 - val_accuracy: 0.3426
Epoch 7808/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0167 - accuracy: 1.0000 - val_loss: 7.3510 - val_accuracy: 0.3427
Epoch 7809/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0167 - accuracy: 1.0000 - val_loss: 7.3522 - val_accuracy: 0.3428
Epoch 7810/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0167 - accuracy: 1.0000 - val_loss: 7.3534 - val_accuracy: 0.3429
Epoch 7811/10000
1/1 [==============================] - 0s 104ms/step - loss: 0.0167 - accuracy: 1.0000 - val_loss: 7.3543 - val_accuracy: 0.3427
Epoch 7812/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0167 - accuracy: 1.0000 - val_loss: 7.3550 - val_accuracy: 0.3428
Epoch 7813/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0166 - accuracy: 1.0000 - val_loss: 7.3560 - val_accuracy: 0.3428
Epoch 7814/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0166 - accuracy: 1.0000 - val_loss: 7.3572 - val_accuracy: 0.3427
Epoch 7815/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0166 - accuracy: 1.0000 - val_loss: 7.3584 - val_accuracy: 0.3427
Epoch 7816/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0166 - accuracy: 1.0000 - val_loss: 7.3598 - val_accuracy: 0.3428
Epoch 7817/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0166 - accuracy: 1.0000 - val_loss: 7.3610 - val_accuracy: 0.3428
Epoch 7818/10000
1/1 [==============================] - 0s 116ms/step - loss: 0.0166 - accuracy: 1.0000 - val_loss: 7.3619 - val_accuracy: 0.3428
Epoch 7819/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0165 - accuracy: 1.0000 - val_loss: 7.3625 - val_accuracy: 0.3427
Epoch 7820/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0165 - accuracy: 1.0000 - val_loss: 7.3632 - val_accuracy: 0.3430
Epoch 7821/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0165 - accuracy: 1.0000 - val_loss: 7.3641 - val_accuracy: 0.3429
Epoch 7822/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0165 - accuracy: 1.0000 - val_loss: 7.3652 - val_accuracy: 0.3428
Epoch 7823/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0165 - accuracy: 1.0000 - val_loss: 7.3662 - val_accuracy: 0.3429
Epoch 7824/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0164 - accuracy: 1.0000 - val_loss: 7.3671 - val_accuracy: 0.3428
Epoch 7825/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0164 - accuracy: 1.0000 - val_loss: 7.3682 - val_accuracy: 0.3428
Epoch 7826/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0164 - accuracy: 1.0000 - val_loss: 7.3693 - val_accuracy: 0.3431
Epoch 7827/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0164 - accuracy: 1.0000 - val_loss: 7.3705 - val_accuracy: 0.3428
Epoch 7828/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0164 - accuracy: 1.0000 - val_loss: 7.3715 - val_accuracy: 0.3429
Epoch 7829/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0164 - accuracy: 1.0000 - val_loss: 7.3724 - val_accuracy: 0.3431
Epoch 7830/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0163 - accuracy: 1.0000 - val_loss: 7.3732 - val_accuracy: 0.3430
Epoch 7831/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0163 - accuracy: 1.0000 - val_loss: 7.3741 - val_accuracy: 0.3429
Epoch 7832/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0163 - accuracy: 1.0000 - val_loss: 7.3750 - val_accuracy: 0.3431
Epoch 7833/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0163 - accuracy: 1.0000 - val_loss: 7.3761 - val_accuracy: 0.3429
Epoch 7834/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0163 - accuracy: 1.0000 - val_loss: 7.3772 - val_accuracy: 0.3429
Epoch 7835/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0162 - accuracy: 1.0000 - val_loss: 7.3782 - val_accuracy: 0.3430
Epoch 7836/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0162 - accuracy: 1.0000 - val_loss: 7.3791 - val_accuracy: 0.3429
Epoch 7837/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0162 - accuracy: 1.0000 - val_loss: 7.3801 - val_accuracy: 0.3429
Epoch 7838/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0162 - accuracy: 1.0000 - val_loss: 7.3811 - val_accuracy: 0.3429
Epoch 7839/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0162 - accuracy: 1.0000 - val_loss: 7.3824 - val_accuracy: 0.3430
Epoch 7840/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0162 - accuracy: 1.0000 - val_loss: 7.3836 - val_accuracy: 0.3430
Epoch 7841/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0161 - accuracy: 1.0000 - val_loss: 7.3846 - val_accuracy: 0.3429
Epoch 7842/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0161 - accuracy: 1.0000 - val_loss: 7.3854 - val_accuracy: 0.3429
Epoch 7843/10000
1/1 [==============================] - 0s 103ms/step - loss: 0.0161 - accuracy: 1.0000 - val_loss: 7.3863 - val_accuracy: 0.3430
Epoch 7844/10000
1/1 [==============================] - 0s 103ms/step - loss: 0.0161 - accuracy: 1.0000 - val_loss: 7.3873 - val_accuracy: 0.3430
Epoch 7845/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0161 - accuracy: 1.0000 - val_loss: 7.3883 - val_accuracy: 0.3430
Epoch 7846/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0161 - accuracy: 1.0000 - val_loss: 7.3893 - val_accuracy: 0.3430
Epoch 7847/10000
1/1 [==============================] - 0s 117ms/step - loss: 0.0160 - accuracy: 1.0000 - val_loss: 7.3902 - val_accuracy: 0.3429
Epoch 7848/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0160 - accuracy: 1.0000 - val_loss: 7.3911 - val_accuracy: 0.3429
Epoch 7849/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0160 - accuracy: 1.0000 - val_loss: 7.3921 - val_accuracy: 0.3431
Epoch 7850/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0160 - accuracy: 1.0000 - val_loss: 7.3931 - val_accuracy: 0.3431
Epoch 7851/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0160 - accuracy: 1.0000 - val_loss: 7.3938 - val_accuracy: 0.3430
Epoch 7852/10000
1/1 [==============================] - 0s 116ms/step - loss: 0.0160 - accuracy: 1.0000 - val_loss: 7.3947 - val_accuracy: 0.3431
Epoch 7853/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0159 - accuracy: 1.0000 - val_loss: 7.3960 - val_accuracy: 0.3430
Epoch 7854/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0159 - accuracy: 1.0000 - val_loss: 7.3972 - val_accuracy: 0.3430
Epoch 7855/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0159 - accuracy: 1.0000 - val_loss: 7.3985 - val_accuracy: 0.3430
Epoch 7856/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0159 - accuracy: 1.0000 - val_loss: 7.3994 - val_accuracy: 0.3430
Epoch 7857/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0159 - accuracy: 1.0000 - val_loss: 7.4002 - val_accuracy: 0.3430
Epoch 7858/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0159 - accuracy: 1.0000 - val_loss: 7.4011 - val_accuracy: 0.3430
Epoch 7859/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0158 - accuracy: 1.0000 - val_loss: 7.4021 - val_accuracy: 0.3429
Epoch 7860/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0158 - accuracy: 1.0000 - val_loss: 7.4031 - val_accuracy: 0.3429
Epoch 7861/10000
1/1 [==============================] - 0s 120ms/step - loss: 0.0158 - accuracy: 1.0000 - val_loss: 7.4042 - val_accuracy: 0.3430
Epoch 7862/10000
1/1 [==============================] - 0s 118ms/step - loss: 0.0158 - accuracy: 1.0000 - val_loss: 7.4050 - val_accuracy: 0.3430
Epoch 7863/10000
1/1 [==============================] - 0s 123ms/step - loss: 0.0158 - accuracy: 1.0000 - val_loss: 7.4059 - val_accuracy: 0.3430
Epoch 7864/10000
1/1 [==============================] - 0s 127ms/step - loss: 0.0158 - accuracy: 1.0000 - val_loss: 7.4066 - val_accuracy: 0.3430
Epoch 7865/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0157 - accuracy: 1.0000 - val_loss: 7.4076 - val_accuracy: 0.3430
Epoch 7866/10000
1/1 [==============================] - 0s 119ms/step - loss: 0.0157 - accuracy: 1.0000 - val_loss: 7.4087 - val_accuracy: 0.3429
Epoch 7867/10000
1/1 [==============================] - 0s 123ms/step - loss: 0.0157 - accuracy: 1.0000 - val_loss: 7.4097 - val_accuracy: 0.3429
Epoch 7868/10000
1/1 [==============================] - 0s 118ms/step - loss: 0.0157 - accuracy: 1.0000 - val_loss: 7.4106 - val_accuracy: 0.3429
Epoch 7869/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0157 - accuracy: 1.0000 - val_loss: 7.4112 - val_accuracy: 0.3429
Epoch 7870/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0157 - accuracy: 1.0000 - val_loss: 7.4120 - val_accuracy: 0.3430
Epoch 7871/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0156 - accuracy: 1.0000 - val_loss: 7.4131 - val_accuracy: 0.3430
Epoch 7872/10000
1/1 [==============================] - 0s 118ms/step - loss: 0.0156 - accuracy: 1.0000 - val_loss: 7.4145 - val_accuracy: 0.3429
Epoch 7873/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0156 - accuracy: 1.0000 - val_loss: 7.4158 - val_accuracy: 0.3429
Epoch 7874/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0156 - accuracy: 1.0000 - val_loss: 7.4169 - val_accuracy: 0.3429
Epoch 7875/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0156 - accuracy: 1.0000 - val_loss: 7.4179 - val_accuracy: 0.3428
Epoch 7876/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0155 - accuracy: 1.0000 - val_loss: 7.4189 - val_accuracy: 0.3429
Epoch 7877/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0155 - accuracy: 1.0000 - val_loss: 7.4199 - val_accuracy: 0.3429
Epoch 7878/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0155 - accuracy: 1.0000 - val_loss: 7.4209 - val_accuracy: 0.3429
Epoch 7879/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0155 - accuracy: 1.0000 - val_loss: 7.4216 - val_accuracy: 0.3429
Epoch 7880/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0155 - accuracy: 1.0000 - val_loss: 7.4224 - val_accuracy: 0.3429
Epoch 7881/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0155 - accuracy: 1.0000 - val_loss: 7.4234 - val_accuracy: 0.3429
Epoch 7882/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0155 - accuracy: 1.0000 - val_loss: 7.4245 - val_accuracy: 0.3429
Epoch 7883/10000
1/1 [==============================] - 0s 117ms/step - loss: 0.0154 - accuracy: 1.0000 - val_loss: 7.4257 - val_accuracy: 0.3429
Epoch 7884/10000
1/1 [==============================] - 0s 120ms/step - loss: 0.0154 - accuracy: 1.0000 - val_loss: 7.4269 - val_accuracy: 0.3428
Epoch 7885/10000
1/1 [==============================] - 0s 117ms/step - loss: 0.0154 - accuracy: 1.0000 - val_loss: 7.4279 - val_accuracy: 0.3429
Epoch 7886/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0154 - accuracy: 1.0000 - val_loss: 7.4289 - val_accuracy: 0.3429
Epoch 7887/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0154 - accuracy: 1.0000 - val_loss: 7.4297 - val_accuracy: 0.3429
Epoch 7888/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0154 - accuracy: 1.0000 - val_loss: 7.4306 - val_accuracy: 0.3429
Epoch 7889/10000
1/1 [==============================] - 0s 116ms/step - loss: 0.0153 - accuracy: 1.0000 - val_loss: 7.4317 - val_accuracy: 0.3428
Epoch 7890/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0153 - accuracy: 1.0000 - val_loss: 7.4327 - val_accuracy: 0.3427
Epoch 7891/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0153 - accuracy: 1.0000 - val_loss: 7.4334 - val_accuracy: 0.3429
Epoch 7892/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0153 - accuracy: 1.0000 - val_loss: 7.4342 - val_accuracy: 0.3429
Epoch 7893/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0153 - accuracy: 1.0000 - val_loss: 7.4351 - val_accuracy: 0.3428
Epoch 7894/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0153 - accuracy: 1.0000 - val_loss: 7.4362 - val_accuracy: 0.3429
Epoch 7895/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0152 - accuracy: 1.0000 - val_loss: 7.4375 - val_accuracy: 0.3429
Epoch 7896/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0152 - accuracy: 1.0000 - val_loss: 7.4386 - val_accuracy: 0.3428
Epoch 7897/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0152 - accuracy: 1.0000 - val_loss: 7.4392 - val_accuracy: 0.3428
Epoch 7898/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0152 - accuracy: 1.0000 - val_loss: 7.4398 - val_accuracy: 0.3429
Epoch 7899/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0152 - accuracy: 1.0000 - val_loss: 7.4407 - val_accuracy: 0.3430
Epoch 7900/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0152 - accuracy: 1.0000 - val_loss: 7.4418 - val_accuracy: 0.3430
Epoch 7901/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0151 - accuracy: 1.0000 - val_loss: 7.4431 - val_accuracy: 0.3430
Epoch 7902/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0151 - accuracy: 1.0000 - val_loss: 7.4444 - val_accuracy: 0.3429
Epoch 7903/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0151 - accuracy: 1.0000 - val_loss: 7.4454 - val_accuracy: 0.3431
Epoch 7904/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0151 - accuracy: 1.0000 - val_loss: 7.4464 - val_accuracy: 0.3430
Epoch 7905/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0151 - accuracy: 1.0000 - val_loss: 7.4473 - val_accuracy: 0.3430
Epoch 7906/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0151 - accuracy: 1.0000 - val_loss: 7.4481 - val_accuracy: 0.3430
Epoch 7907/10000
1/1 [==============================] - 0s 123ms/step - loss: 0.0150 - accuracy: 1.0000 - val_loss: 7.4488 - val_accuracy: 0.3429
Epoch 7908/10000
1/1 [==============================] - 0s 119ms/step - loss: 0.0150 - accuracy: 1.0000 - val_loss: 7.4497 - val_accuracy: 0.3430
Epoch 7909/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0150 - accuracy: 1.0000 - val_loss: 7.4506 - val_accuracy: 0.3430
Epoch 7910/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0150 - accuracy: 1.0000 - val_loss: 7.4516 - val_accuracy: 0.3429
Epoch 7911/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0150 - accuracy: 1.0000 - val_loss: 7.4525 - val_accuracy: 0.3429
Epoch 7912/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0150 - accuracy: 1.0000 - val_loss: 7.4535 - val_accuracy: 0.3430
Epoch 7913/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0150 - accuracy: 1.0000 - val_loss: 7.4546 - val_accuracy: 0.3430
Epoch 7914/10000
1/1 [==============================] - 0s 119ms/step - loss: 0.0149 - accuracy: 1.0000 - val_loss: 7.4557 - val_accuracy: 0.3429
Epoch 7915/10000
1/1 [==============================] - 0s 123ms/step - loss: 0.0149 - accuracy: 1.0000 - val_loss: 7.4568 - val_accuracy: 0.3428
Epoch 7916/10000
1/1 [==============================] - 0s 116ms/step - loss: 0.0149 - accuracy: 1.0000 - val_loss: 7.4577 - val_accuracy: 0.3428
Epoch 7917/10000
1/1 [==============================] - 0s 117ms/step - loss: 0.0149 - accuracy: 1.0000 - val_loss: 7.4584 - val_accuracy: 0.3428
Epoch 7918/10000
1/1 [==============================] - 0s 118ms/step - loss: 0.0149 - accuracy: 1.0000 - val_loss: 7.4592 - val_accuracy: 0.3428
Epoch 7919/10000
1/1 [==============================] - 0s 118ms/step - loss: 0.0149 - accuracy: 1.0000 - val_loss: 7.4602 - val_accuracy: 0.3428
Epoch 7920/10000
1/1 [==============================] - 0s 121ms/step - loss: 0.0148 - accuracy: 1.0000 - val_loss: 7.4614 - val_accuracy: 0.3428
Epoch 7921/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0148 - accuracy: 1.0000 - val_loss: 7.4626 - val_accuracy: 0.3428
Epoch 7922/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0148 - accuracy: 1.0000 - val_loss: 7.4638 - val_accuracy: 0.3428
Epoch 7923/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0148 - accuracy: 1.0000 - val_loss: 7.4649 - val_accuracy: 0.3428
Epoch 7924/10000
1/1 [==============================] - 0s 119ms/step - loss: 0.0148 - accuracy: 1.0000 - val_loss: 7.4659 - val_accuracy: 0.3428
Epoch 7925/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0148 - accuracy: 1.0000 - val_loss: 7.4666 - val_accuracy: 0.3428
Epoch 7926/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0147 - accuracy: 1.0000 - val_loss: 7.4671 - val_accuracy: 0.3428
Epoch 7927/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0147 - accuracy: 1.0000 - val_loss: 7.4679 - val_accuracy: 0.3428
Epoch 7928/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0147 - accuracy: 1.0000 - val_loss: 7.4688 - val_accuracy: 0.3426
Epoch 7929/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0147 - accuracy: 1.0000 - val_loss: 7.4700 - val_accuracy: 0.3427
Epoch 7930/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0147 - accuracy: 1.0000 - val_loss: 7.4710 - val_accuracy: 0.3426
Epoch 7931/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0147 - accuracy: 1.0000 - val_loss: 7.4718 - val_accuracy: 0.3426
Epoch 7932/10000
1/1 [==============================] - 0s 104ms/step - loss: 0.0147 - accuracy: 1.0000 - val_loss: 7.4726 - val_accuracy: 0.3427
Epoch 7933/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0146 - accuracy: 1.0000 - val_loss: 7.4737 - val_accuracy: 0.3427
Epoch 7934/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0146 - accuracy: 1.0000 - val_loss: 7.4748 - val_accuracy: 0.3427
Epoch 7935/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0146 - accuracy: 1.0000 - val_loss: 7.4761 - val_accuracy: 0.3427
Epoch 7936/10000
1/1 [==============================] - 0s 104ms/step - loss: 0.0146 - accuracy: 1.0000 - val_loss: 7.4773 - val_accuracy: 0.3426
Epoch 7937/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0146 - accuracy: 1.0000 - val_loss: 7.4783 - val_accuracy: 0.3427
Epoch 7938/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0146 - accuracy: 1.0000 - val_loss: 7.4791 - val_accuracy: 0.3427
Epoch 7939/10000
1/1 [==============================] - 0s 104ms/step - loss: 0.0145 - accuracy: 1.0000 - val_loss: 7.4798 - val_accuracy: 0.3428
Epoch 7940/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0145 - accuracy: 1.0000 - val_loss: 7.4807 - val_accuracy: 0.3428
Epoch 7941/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0145 - accuracy: 1.0000 - val_loss: 7.4817 - val_accuracy: 0.3428
Epoch 7942/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0145 - accuracy: 1.0000 - val_loss: 7.4828 - val_accuracy: 0.3427
Epoch 7943/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0145 - accuracy: 1.0000 - val_loss: 7.4835 - val_accuracy: 0.3426
Epoch 7944/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0145 - accuracy: 1.0000 - val_loss: 7.4842 - val_accuracy: 0.3425
Epoch 7945/10000
1/1 [==============================] - 0s 103ms/step - loss: 0.0145 - accuracy: 1.0000 - val_loss: 7.4848 - val_accuracy: 0.3425
Epoch 7946/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0144 - accuracy: 1.0000 - val_loss: 7.4858 - val_accuracy: 0.3423
Epoch 7947/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0144 - accuracy: 1.0000 - val_loss: 7.4870 - val_accuracy: 0.3425
Epoch 7948/10000
1/1 [==============================] - 0s 103ms/step - loss: 0.0144 - accuracy: 1.0000 - val_loss: 7.4883 - val_accuracy: 0.3424
Epoch 7949/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0144 - accuracy: 1.0000 - val_loss: 7.4896 - val_accuracy: 0.3425
Epoch 7950/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0144 - accuracy: 1.0000 - val_loss: 7.4907 - val_accuracy: 0.3424
Epoch 7951/10000
1/1 [==============================] - 0s 104ms/step - loss: 0.0144 - accuracy: 1.0000 - val_loss: 7.4915 - val_accuracy: 0.3424
Epoch 7952/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0144 - accuracy: 1.0000 - val_loss: 7.4923 - val_accuracy: 0.3424
Epoch 7953/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0143 - accuracy: 1.0000 - val_loss: 7.4931 - val_accuracy: 0.3425
Epoch 7954/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0143 - accuracy: 1.0000 - val_loss: 7.4940 - val_accuracy: 0.3425
Epoch 7955/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0143 - accuracy: 1.0000 - val_loss: 7.4950 - val_accuracy: 0.3426
Epoch 7956/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0143 - accuracy: 1.0000 - val_loss: 7.4960 - val_accuracy: 0.3425
Epoch 7957/10000
1/1 [==============================] - 0s 117ms/step - loss: 0.0143 - accuracy: 1.0000 - val_loss: 7.4970 - val_accuracy: 0.3425
Epoch 7958/10000
1/1 [==============================] - 0s 119ms/step - loss: 0.0143 - accuracy: 1.0000 - val_loss: 7.4980 - val_accuracy: 0.3424
Epoch 7959/10000
1/1 [==============================] - 0s 116ms/step - loss: 0.0142 - accuracy: 1.0000 - val_loss: 7.4986 - val_accuracy: 0.3424
Epoch 7960/10000
1/1 [==============================] - 0s 119ms/step - loss: 0.0142 - accuracy: 1.0000 - val_loss: 7.4993 - val_accuracy: 0.3424
Epoch 7961/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0142 - accuracy: 1.0000 - val_loss: 7.5003 - val_accuracy: 0.3424
Epoch 7962/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0142 - accuracy: 1.0000 - val_loss: 7.5014 - val_accuracy: 0.3424
Epoch 7963/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0142 - accuracy: 1.0000 - val_loss: 7.5025 - val_accuracy: 0.3424
Epoch 7964/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0142 - accuracy: 1.0000 - val_loss: 7.5038 - val_accuracy: 0.3425
Epoch 7965/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0142 - accuracy: 1.0000 - val_loss: 7.5047 - val_accuracy: 0.3423
Epoch 7966/10000
1/1 [==============================] - 0s 123ms/step - loss: 0.0141 - accuracy: 1.0000 - val_loss: 7.5056 - val_accuracy: 0.3423
Epoch 7967/10000
1/1 [==============================] - 0s 126ms/step - loss: 0.0141 - accuracy: 1.0000 - val_loss: 7.5064 - val_accuracy: 0.3422
Epoch 7968/10000
1/1 [==============================] - 0s 126ms/step - loss: 0.0141 - accuracy: 1.0000 - val_loss: 7.5073 - val_accuracy: 0.3423
Epoch 7969/10000
1/1 [==============================] - 0s 122ms/step - loss: 0.0141 - accuracy: 1.0000 - val_loss: 7.5083 - val_accuracy: 0.3423
Epoch 7970/10000
1/1 [==============================] - 0s 125ms/step - loss: 0.0141 - accuracy: 1.0000 - val_loss: 7.5094 - val_accuracy: 0.3425
Epoch 7971/10000
1/1 [==============================] - 0s 120ms/step - loss: 0.0141 - accuracy: 1.0000 - val_loss: 7.5101 - val_accuracy: 0.3424
Epoch 7972/10000
1/1 [==============================] - 0s 118ms/step - loss: 0.0141 - accuracy: 1.0000 - val_loss: 7.5110 - val_accuracy: 0.3425
Epoch 7973/10000
1/1 [==============================] - 0s 129ms/step - loss: 0.0140 - accuracy: 1.0000 - val_loss: 7.5119 - val_accuracy: 0.3425
Epoch 7974/10000
1/1 [==============================] - 0s 121ms/step - loss: 0.0140 - accuracy: 1.0000 - val_loss: 7.5129 - val_accuracy: 0.3425
Epoch 7975/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0140 - accuracy: 1.0000 - val_loss: 7.5138 - val_accuracy: 0.3424
Epoch 7976/10000
1/1 [==============================] - 0s 137ms/step - loss: 0.0140 - accuracy: 1.0000 - val_loss: 7.5150 - val_accuracy: 0.3423
Epoch 7977/10000
1/1 [==============================] - 0s 131ms/step - loss: 0.0140 - accuracy: 1.0000 - val_loss: 7.5159 - val_accuracy: 0.3423
Epoch 7978/10000
1/1 [==============================] - 0s 124ms/step - loss: 0.0140 - accuracy: 1.0000 - val_loss: 7.5168 - val_accuracy: 0.3424
Epoch 7979/10000
1/1 [==============================] - 0s 129ms/step - loss: 0.0140 - accuracy: 1.0000 - val_loss: 7.5179 - val_accuracy: 0.3424
Epoch 7980/10000
1/1 [==============================] - 0s 127ms/step - loss: 0.0139 - accuracy: 1.0000 - val_loss: 7.5189 - val_accuracy: 0.3424
Epoch 7981/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0139 - accuracy: 1.0000 - val_loss: 7.5197 - val_accuracy: 0.3425
Epoch 7982/10000
1/1 [==============================] - 0s 120ms/step - loss: 0.0139 - accuracy: 1.0000 - val_loss: 7.5205 - val_accuracy: 0.3424
Epoch 7983/10000
1/1 [==============================] - 0s 121ms/step - loss: 0.0139 - accuracy: 1.0000 - val_loss: 7.5216 - val_accuracy: 0.3423
Epoch 7984/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0139 - accuracy: 1.0000 - val_loss: 7.5226 - val_accuracy: 0.3423
Epoch 7985/10000
1/1 [==============================] - 0s 118ms/step - loss: 0.0139 - accuracy: 1.0000 - val_loss: 7.5237 - val_accuracy: 0.3424
Epoch 7986/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0139 - accuracy: 1.0000 - val_loss: 7.5247 - val_accuracy: 0.3424
Epoch 7987/10000
1/1 [==============================] - 0s 118ms/step - loss: 0.0138 - accuracy: 1.0000 - val_loss: 7.5256 - val_accuracy: 0.3423
Epoch 7988/10000
1/1 [==============================] - 0s 116ms/step - loss: 0.0138 - accuracy: 1.0000 - val_loss: 7.5263 - val_accuracy: 0.3424
Epoch 7989/10000
1/1 [==============================] - 0s 122ms/step - loss: 0.0138 - accuracy: 1.0000 - val_loss: 7.5272 - val_accuracy: 0.3423
Epoch 7990/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0138 - accuracy: 1.0000 - val_loss: 7.5282 - val_accuracy: 0.3425
Epoch 7991/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0138 - accuracy: 1.0000 - val_loss: 7.5293 - val_accuracy: 0.3424
Epoch 7992/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0138 - accuracy: 1.0000 - val_loss: 7.5303 - val_accuracy: 0.3424
Epoch 7993/10000
1/1 [==============================] - 0s 118ms/step - loss: 0.0138 - accuracy: 1.0000 - val_loss: 7.5312 - val_accuracy: 0.3422
Epoch 7994/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0137 - accuracy: 1.0000 - val_loss: 7.5321 - val_accuracy: 0.3423
Epoch 7995/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0137 - accuracy: 1.0000 - val_loss: 7.5326 - val_accuracy: 0.3424
Epoch 7996/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0137 - accuracy: 1.0000 - val_loss: 7.5336 - val_accuracy: 0.3425
Epoch 7997/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0137 - accuracy: 1.0000 - val_loss: 7.5344 - val_accuracy: 0.3424
Epoch 7998/10000
1/1 [==============================] - 0s 118ms/step - loss: 0.0137 - accuracy: 1.0000 - val_loss: 7.5355 - val_accuracy: 0.3426
Epoch 7999/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0137 - accuracy: 1.0000 - val_loss: 7.5366 - val_accuracy: 0.3425
Epoch 8000/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0137 - accuracy: 1.0000 - val_loss: 7.5377 - val_accuracy: 0.3425
Epoch 8001/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0136 - accuracy: 1.0000 - val_loss: 7.5387 - val_accuracy: 0.3427
Epoch 8002/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0136 - accuracy: 1.0000 - val_loss: 7.5396 - val_accuracy: 0.3426
Epoch 8003/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0136 - accuracy: 1.0000 - val_loss: 7.5407 - val_accuracy: 0.3425
Epoch 8004/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0136 - accuracy: 1.0000 - val_loss: 7.5417 - val_accuracy: 0.3427
Epoch 8005/10000
1/1 [==============================] - 0s 117ms/step - loss: 0.0136 - accuracy: 1.0000 - val_loss: 7.5425 - val_accuracy: 0.3428
Epoch 8006/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0136 - accuracy: 1.0000 - val_loss: 7.5432 - val_accuracy: 0.3424
Epoch 8007/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0136 - accuracy: 1.0000 - val_loss: 7.5440 - val_accuracy: 0.3426
Epoch 8008/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0135 - accuracy: 1.0000 - val_loss: 7.5450 - val_accuracy: 0.3426
Epoch 8009/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0135 - accuracy: 1.0000 - val_loss: 7.5461 - val_accuracy: 0.3427
Epoch 8010/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0135 - accuracy: 1.0000 - val_loss: 7.5473 - val_accuracy: 0.3428
Epoch 8011/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0135 - accuracy: 1.0000 - val_loss: 7.5481 - val_accuracy: 0.3428
Epoch 8012/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0135 - accuracy: 1.0000 - val_loss: 7.5486 - val_accuracy: 0.3426
Epoch 8013/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0135 - accuracy: 1.0000 - val_loss: 7.5493 - val_accuracy: 0.3428
Epoch 8014/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0135 - accuracy: 1.0000 - val_loss: 7.5503 - val_accuracy: 0.3428
Epoch 8015/10000
1/1 [==============================] - 0s 117ms/step - loss: 0.0134 - accuracy: 1.0000 - val_loss: 7.5515 - val_accuracy: 0.3429
Epoch 8016/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0134 - accuracy: 1.0000 - val_loss: 7.5525 - val_accuracy: 0.3431
Epoch 8017/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0134 - accuracy: 1.0000 - val_loss: 7.5536 - val_accuracy: 0.3431
Epoch 8018/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0134 - accuracy: 1.0000 - val_loss: 7.5545 - val_accuracy: 0.3428
Epoch 8019/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0134 - accuracy: 1.0000 - val_loss: 7.5553 - val_accuracy: 0.3428
Epoch 8020/10000
1/1 [==============================] - 0s 119ms/step - loss: 0.0134 - accuracy: 1.0000 - val_loss: 7.5563 - val_accuracy: 0.3428
Epoch 8021/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0134 - accuracy: 1.0000 - val_loss: 7.5573 - val_accuracy: 0.3428
Epoch 8022/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0134 - accuracy: 1.0000 - val_loss: 7.5584 - val_accuracy: 0.3429
Epoch 8023/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0133 - accuracy: 1.0000 - val_loss: 7.5594 - val_accuracy: 0.3429
Epoch 8024/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0133 - accuracy: 1.0000 - val_loss: 7.5602 - val_accuracy: 0.3429
Epoch 8025/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0133 - accuracy: 1.0000 - val_loss: 7.5610 - val_accuracy: 0.3429
Epoch 8026/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0133 - accuracy: 1.0000 - val_loss: 7.5619 - val_accuracy: 0.3428
Epoch 8027/10000
1/1 [==============================] - 0s 118ms/step - loss: 0.0133 - accuracy: 1.0000 - val_loss: 7.5631 - val_accuracy: 0.3429
Epoch 8028/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0133 - accuracy: 1.0000 - val_loss: 7.5642 - val_accuracy: 0.3429
Epoch 8029/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0133 - accuracy: 1.0000 - val_loss: 7.5652 - val_accuracy: 0.3428
Epoch 8030/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0132 - accuracy: 1.0000 - val_loss: 7.5659 - val_accuracy: 0.3429
Epoch 8031/10000
1/1 [==============================] - 0s 104ms/step - loss: 0.0132 - accuracy: 1.0000 - val_loss: 7.5666 - val_accuracy: 0.3428
Epoch 8032/10000
1/1 [==============================] - 0s 103ms/step - loss: 0.0132 - accuracy: 1.0000 - val_loss: 7.5673 - val_accuracy: 0.3427
Epoch 8033/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0132 - accuracy: 1.0000 - val_loss: 7.5683 - val_accuracy: 0.3430
Epoch 8034/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0132 - accuracy: 1.0000 - val_loss: 7.5695 - val_accuracy: 0.3430
Epoch 8035/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0132 - accuracy: 1.0000 - val_loss: 7.5704 - val_accuracy: 0.3430
Epoch 8036/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0132 - accuracy: 1.0000 - val_loss: 7.5711 - val_accuracy: 0.3431
Epoch 8037/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0131 - accuracy: 1.0000 - val_loss: 7.5720 - val_accuracy: 0.3431
Epoch 8038/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0131 - accuracy: 1.0000 - val_loss: 7.5729 - val_accuracy: 0.3430
Epoch 8039/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0131 - accuracy: 1.0000 - val_loss: 7.5741 - val_accuracy: 0.3432
Epoch 8040/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0131 - accuracy: 1.0000 - val_loss: 7.5752 - val_accuracy: 0.3430
Epoch 8041/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0131 - accuracy: 1.0000 - val_loss: 7.5763 - val_accuracy: 0.3430
Epoch 8042/10000
1/1 [==============================] - 0s 117ms/step - loss: 0.0131 - accuracy: 1.0000 - val_loss: 7.5772 - val_accuracy: 0.3429
Epoch 8043/10000
1/1 [==============================] - 0s 116ms/step - loss: 0.0131 - accuracy: 1.0000 - val_loss: 7.5779 - val_accuracy: 0.3429
Epoch 8044/10000
1/1 [==============================] - 0s 117ms/step - loss: 0.0131 - accuracy: 1.0000 - val_loss: 7.5788 - val_accuracy: 0.3429
Epoch 8045/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0130 - accuracy: 1.0000 - val_loss: 7.5797 - val_accuracy: 0.3430
Epoch 8046/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0130 - accuracy: 1.0000 - val_loss: 7.5809 - val_accuracy: 0.3431
Epoch 8047/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0130 - accuracy: 1.0000 - val_loss: 7.5816 - val_accuracy: 0.3430
Epoch 8048/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0130 - accuracy: 1.0000 - val_loss: 7.5824 - val_accuracy: 0.3430
Epoch 8049/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0130 - accuracy: 1.0000 - val_loss: 7.5834 - val_accuracy: 0.3432
Epoch 8050/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0130 - accuracy: 1.0000 - val_loss: 7.5846 - val_accuracy: 0.3431
Epoch 8051/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0130 - accuracy: 1.0000 - val_loss: 7.5854 - val_accuracy: 0.3429
Epoch 8052/10000
1/1 [==============================] - 0s 126ms/step - loss: 0.0129 - accuracy: 1.0000 - val_loss: 7.5863 - val_accuracy: 0.3430
Epoch 8053/10000
1/1 [==============================] - 0s 125ms/step - loss: 0.0129 - accuracy: 1.0000 - val_loss: 7.5873 - val_accuracy: 0.3429
Epoch 8054/10000
1/1 [==============================] - 0s 118ms/step - loss: 0.0129 - accuracy: 1.0000 - val_loss: 7.5883 - val_accuracy: 0.3429
Epoch 8055/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0129 - accuracy: 1.0000 - val_loss: 7.5892 - val_accuracy: 0.3431
Epoch 8056/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0129 - accuracy: 1.0000 - val_loss: 7.5901 - val_accuracy: 0.3431
Epoch 8057/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0129 - accuracy: 1.0000 - val_loss: 7.5911 - val_accuracy: 0.3432
Epoch 8058/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0129 - accuracy: 1.0000 - val_loss: 7.5920 - val_accuracy: 0.3432
Epoch 8059/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0129 - accuracy: 1.0000 - val_loss: 7.5928 - val_accuracy: 0.3432
Epoch 8060/10000
1/1 [==============================] - 0s 116ms/step - loss: 0.0128 - accuracy: 1.0000 - val_loss: 7.5937 - val_accuracy: 0.3431
Epoch 8061/10000
1/1 [==============================] - 0s 116ms/step - loss: 0.0128 - accuracy: 1.0000 - val_loss: 7.5948 - val_accuracy: 0.3430
Epoch 8062/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0128 - accuracy: 1.0000 - val_loss: 7.5956 - val_accuracy: 0.3429
Epoch 8063/10000
1/1 [==============================] - 0s 118ms/step - loss: 0.0128 - accuracy: 1.0000 - val_loss: 7.5963 - val_accuracy: 0.3429
Epoch 8064/10000
1/1 [==============================] - 0s 116ms/step - loss: 0.0128 - accuracy: 1.0000 - val_loss: 7.5972 - val_accuracy: 0.3431
Epoch 8065/10000
1/1 [==============================] - 0s 118ms/step - loss: 0.0128 - accuracy: 1.0000 - val_loss: 7.5982 - val_accuracy: 0.3430
Epoch 8066/10000
1/1 [==============================] - 0s 117ms/step - loss: 0.0128 - accuracy: 1.0000 - val_loss: 7.5993 - val_accuracy: 0.3431
Epoch 8067/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0128 - accuracy: 1.0000 - val_loss: 7.6003 - val_accuracy: 0.3430
Epoch 8068/10000
1/1 [==============================] - 0s 117ms/step - loss: 0.0127 - accuracy: 1.0000 - val_loss: 7.6012 - val_accuracy: 0.3429
Epoch 8069/10000
1/1 [==============================] - 0s 119ms/step - loss: 0.0127 - accuracy: 1.0000 - val_loss: 7.6020 - val_accuracy: 0.3429
Epoch 8070/10000
1/1 [==============================] - 0s 120ms/step - loss: 0.0127 - accuracy: 1.0000 - val_loss: 7.6030 - val_accuracy: 0.3427
Epoch 8071/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0127 - accuracy: 1.0000 - val_loss: 7.6040 - val_accuracy: 0.3428
Epoch 8072/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0127 - accuracy: 1.0000 - val_loss: 7.6050 - val_accuracy: 0.3430
Epoch 8073/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0127 - accuracy: 1.0000 - val_loss: 7.6060 - val_accuracy: 0.3429
Epoch 8074/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0127 - accuracy: 1.0000 - val_loss: 7.6069 - val_accuracy: 0.3430
Epoch 8075/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0126 - accuracy: 1.0000 - val_loss: 7.6076 - val_accuracy: 0.3429
Epoch 8076/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0126 - accuracy: 1.0000 - val_loss: 7.6084 - val_accuracy: 0.3429
Epoch 8077/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0126 - accuracy: 1.0000 - val_loss: 7.6092 - val_accuracy: 0.3427
Epoch 8078/10000
1/1 [==============================] - 0s 120ms/step - loss: 0.0126 - accuracy: 1.0000 - val_loss: 7.6101 - val_accuracy: 0.3430
Epoch 8079/10000
1/1 [==============================] - 0s 116ms/step - loss: 0.0126 - accuracy: 1.0000 - val_loss: 7.6110 - val_accuracy: 0.3428
Epoch 8080/10000
1/1 [==============================] - 0s 116ms/step - loss: 0.0126 - accuracy: 1.0000 - val_loss: 7.6121 - val_accuracy: 0.3429
Epoch 8081/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0126 - accuracy: 1.0000 - val_loss: 7.6129 - val_accuracy: 0.3429
Epoch 8082/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0126 - accuracy: 1.0000 - val_loss: 7.6137 - val_accuracy: 0.3428
Epoch 8083/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0125 - accuracy: 1.0000 - val_loss: 7.6146 - val_accuracy: 0.3428
Epoch 8084/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0125 - accuracy: 1.0000 - val_loss: 7.6156 - val_accuracy: 0.3430
Epoch 8085/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0125 - accuracy: 1.0000 - val_loss: 7.6168 - val_accuracy: 0.3430
Epoch 8086/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0125 - accuracy: 1.0000 - val_loss: 7.6177 - val_accuracy: 0.3431
Epoch 8087/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0125 - accuracy: 1.0000 - val_loss: 7.6186 - val_accuracy: 0.3431
Epoch 8088/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0125 - accuracy: 1.0000 - val_loss: 7.6198 - val_accuracy: 0.3429
Epoch 8089/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0125 - accuracy: 1.0000 - val_loss: 7.6208 - val_accuracy: 0.3431
Epoch 8090/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0125 - accuracy: 1.0000 - val_loss: 7.6216 - val_accuracy: 0.3428
Epoch 8091/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0124 - accuracy: 1.0000 - val_loss: 7.6224 - val_accuracy: 0.3429
Epoch 8092/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0124 - accuracy: 1.0000 - val_loss: 7.6234 - val_accuracy: 0.3430
Epoch 8093/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0124 - accuracy: 1.0000 - val_loss: 7.6243 - val_accuracy: 0.3428
Epoch 8094/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0124 - accuracy: 1.0000 - val_loss: 7.6251 - val_accuracy: 0.3429
Epoch 8095/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0124 - accuracy: 1.0000 - val_loss: 7.6259 - val_accuracy: 0.3429
Epoch 8096/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0124 - accuracy: 1.0000 - val_loss: 7.6268 - val_accuracy: 0.3429
Epoch 8097/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0124 - accuracy: 1.0000 - val_loss: 7.6278 - val_accuracy: 0.3428
Epoch 8098/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0124 - accuracy: 1.0000 - val_loss: 7.6288 - val_accuracy: 0.3428
Epoch 8099/10000
1/1 [==============================] - 0s 117ms/step - loss: 0.0123 - accuracy: 1.0000 - val_loss: 7.6298 - val_accuracy: 0.3428
Epoch 8100/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0123 - accuracy: 1.0000 - val_loss: 7.6306 - val_accuracy: 0.3429
Epoch 8101/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0123 - accuracy: 1.0000 - val_loss: 7.6313 - val_accuracy: 0.3429
Epoch 8102/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0123 - accuracy: 1.0000 - val_loss: 7.6321 - val_accuracy: 0.3427
Epoch 8103/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0123 - accuracy: 1.0000 - val_loss: 7.6331 - val_accuracy: 0.3427
Epoch 8104/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0123 - accuracy: 1.0000 - val_loss: 7.6339 - val_accuracy: 0.3429
Epoch 8105/10000
1/1 [==============================] - 0s 119ms/step - loss: 0.0123 - accuracy: 1.0000 - val_loss: 7.6349 - val_accuracy: 0.3429
Epoch 8106/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0123 - accuracy: 1.0000 - val_loss: 7.6359 - val_accuracy: 0.3428
Epoch 8107/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0122 - accuracy: 1.0000 - val_loss: 7.6370 - val_accuracy: 0.3428
Epoch 8108/10000
1/1 [==============================] - 0s 116ms/step - loss: 0.0122 - accuracy: 1.0000 - val_loss: 7.6379 - val_accuracy: 0.3428
Epoch 8109/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0122 - accuracy: 1.0000 - val_loss: 7.6388 - val_accuracy: 0.3428
Epoch 8110/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0122 - accuracy: 1.0000 - val_loss: 7.6397 - val_accuracy: 0.3428
Epoch 8111/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0122 - accuracy: 1.0000 - val_loss: 7.6407 - val_accuracy: 0.3428
Epoch 8112/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0122 - accuracy: 1.0000 - val_loss: 7.6416 - val_accuracy: 0.3428
Epoch 8113/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0122 - accuracy: 1.0000 - val_loss: 7.6423 - val_accuracy: 0.3430
Epoch 8114/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0122 - accuracy: 1.0000 - val_loss: 7.6431 - val_accuracy: 0.3429
Epoch 8115/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0121 - accuracy: 1.0000 - val_loss: 7.6440 - val_accuracy: 0.3429
Epoch 8116/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0121 - accuracy: 1.0000 - val_loss: 7.6449 - val_accuracy: 0.3428
Epoch 8117/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0121 - accuracy: 1.0000 - val_loss: 7.6458 - val_accuracy: 0.3428
Epoch 8118/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0121 - accuracy: 1.0000 - val_loss: 7.6469 - val_accuracy: 0.3428
Epoch 8119/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0121 - accuracy: 1.0000 - val_loss: 7.6479 - val_accuracy: 0.3427
Epoch 8120/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0121 - accuracy: 1.0000 - val_loss: 7.6487 - val_accuracy: 0.3427
Epoch 8121/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0121 - accuracy: 1.0000 - val_loss: 7.6494 - val_accuracy: 0.3428
Epoch 8122/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0121 - accuracy: 1.0000 - val_loss: 7.6502 - val_accuracy: 0.3426
Epoch 8123/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0120 - accuracy: 1.0000 - val_loss: 7.6513 - val_accuracy: 0.3427
Epoch 8124/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0120 - accuracy: 1.0000 - val_loss: 7.6523 - val_accuracy: 0.3426
Epoch 8125/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0120 - accuracy: 1.0000 - val_loss: 7.6531 - val_accuracy: 0.3427
Epoch 8126/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0120 - accuracy: 1.0000 - val_loss: 7.6540 - val_accuracy: 0.3427
Epoch 8127/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0120 - accuracy: 1.0000 - val_loss: 7.6549 - val_accuracy: 0.3428
Epoch 8128/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0120 - accuracy: 1.0000 - val_loss: 7.6559 - val_accuracy: 0.3428
Epoch 8129/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0120 - accuracy: 1.0000 - val_loss: 7.6568 - val_accuracy: 0.3428
Epoch 8130/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0120 - accuracy: 1.0000 - val_loss: 7.6577 - val_accuracy: 0.3427
Epoch 8131/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0120 - accuracy: 1.0000 - val_loss: 7.6588 - val_accuracy: 0.3428
Epoch 8132/10000
1/1 [==============================] - 0s 119ms/step - loss: 0.0119 - accuracy: 1.0000 - val_loss: 7.6597 - val_accuracy: 0.3429
Epoch 8133/10000
1/1 [==============================] - 0s 122ms/step - loss: 0.0119 - accuracy: 1.0000 - val_loss: 7.6603 - val_accuracy: 0.3428
Epoch 8134/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0119 - accuracy: 1.0000 - val_loss: 7.6611 - val_accuracy: 0.3427
Epoch 8135/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0119 - accuracy: 1.0000 - val_loss: 7.6621 - val_accuracy: 0.3426
Epoch 8136/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0119 - accuracy: 1.0000 - val_loss: 7.6630 - val_accuracy: 0.3428
Epoch 8137/10000
1/1 [==============================] - 0s 118ms/step - loss: 0.0119 - accuracy: 1.0000 - val_loss: 7.6640 - val_accuracy: 0.3428
Epoch 8138/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0119 - accuracy: 1.0000 - val_loss: 7.6648 - val_accuracy: 0.3428
Epoch 8139/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0119 - accuracy: 1.0000 - val_loss: 7.6655 - val_accuracy: 0.3428
Epoch 8140/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0118 - accuracy: 1.0000 - val_loss: 7.6663 - val_accuracy: 0.3427
Epoch 8141/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0118 - accuracy: 1.0000 - val_loss: 7.6673 - val_accuracy: 0.3429
Epoch 8142/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0118 - accuracy: 1.0000 - val_loss: 7.6684 - val_accuracy: 0.3427
Epoch 8143/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0118 - accuracy: 1.0000 - val_loss: 7.6696 - val_accuracy: 0.3428
Epoch 8144/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0118 - accuracy: 1.0000 - val_loss: 7.6704 - val_accuracy: 0.3427
Epoch 8145/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0118 - accuracy: 1.0000 - val_loss: 7.6711 - val_accuracy: 0.3428
Epoch 8146/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0118 - accuracy: 1.0000 - val_loss: 7.6719 - val_accuracy: 0.3428
Epoch 8147/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0118 - accuracy: 1.0000 - val_loss: 7.6728 - val_accuracy: 0.3427
Epoch 8148/10000
1/1 [==============================] - 0s 117ms/step - loss: 0.0117 - accuracy: 1.0000 - val_loss: 7.6738 - val_accuracy: 0.3427
Epoch 8149/10000
1/1 [==============================] - 0s 117ms/step - loss: 0.0117 - accuracy: 1.0000 - val_loss: 7.6747 - val_accuracy: 0.3428
Epoch 8150/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0117 - accuracy: 1.0000 - val_loss: 7.6755 - val_accuracy: 0.3426
Epoch 8151/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0117 - accuracy: 1.0000 - val_loss: 7.6765 - val_accuracy: 0.3426
Epoch 8152/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0117 - accuracy: 1.0000 - val_loss: 7.6774 - val_accuracy: 0.3427
Epoch 8153/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0117 - accuracy: 1.0000 - val_loss: 7.6783 - val_accuracy: 0.3427
Epoch 8154/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0117 - accuracy: 1.0000 - val_loss: 7.6790 - val_accuracy: 0.3427
Epoch 8155/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0117 - accuracy: 1.0000 - val_loss: 7.6797 - val_accuracy: 0.3425
Epoch 8156/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0117 - accuracy: 1.0000 - val_loss: 7.6807 - val_accuracy: 0.3426
Epoch 8157/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0116 - accuracy: 1.0000 - val_loss: 7.6817 - val_accuracy: 0.3426
Epoch 8158/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0116 - accuracy: 1.0000 - val_loss: 7.6826 - val_accuracy: 0.3427
Epoch 8159/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0116 - accuracy: 1.0000 - val_loss: 7.6834 - val_accuracy: 0.3426
Epoch 8160/10000
1/1 [==============================] - 0s 125ms/step - loss: 0.0116 - accuracy: 1.0000 - val_loss: 7.6842 - val_accuracy: 0.3426
Epoch 8161/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0116 - accuracy: 1.0000 - val_loss: 7.6852 - val_accuracy: 0.3425
Epoch 8162/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0116 - accuracy: 1.0000 - val_loss: 7.6864 - val_accuracy: 0.3426
Epoch 8163/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0116 - accuracy: 1.0000 - val_loss: 7.6875 - val_accuracy: 0.3425
Epoch 8164/10000
1/1 [==============================] - 0s 120ms/step - loss: 0.0116 - accuracy: 1.0000 - val_loss: 7.6883 - val_accuracy: 0.3426
Epoch 8165/10000
1/1 [==============================] - 0s 118ms/step - loss: 0.0116 - accuracy: 1.0000 - val_loss: 7.6891 - val_accuracy: 0.3425
Epoch 8166/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0115 - accuracy: 1.0000 - val_loss: 7.6899 - val_accuracy: 0.3426
Epoch 8167/10000
1/1 [==============================] - 0s 120ms/step - loss: 0.0115 - accuracy: 1.0000 - val_loss: 7.6909 - val_accuracy: 0.3425
Epoch 8168/10000
1/1 [==============================] - 0s 116ms/step - loss: 0.0115 - accuracy: 1.0000 - val_loss: 7.6919 - val_accuracy: 0.3425
Epoch 8169/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0115 - accuracy: 1.0000 - val_loss: 7.6929 - val_accuracy: 0.3426
Epoch 8170/10000
1/1 [==============================] - 0s 122ms/step - loss: 0.0115 - accuracy: 1.0000 - val_loss: 7.6937 - val_accuracy: 0.3426
Epoch 8171/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0115 - accuracy: 1.0000 - val_loss: 7.6945 - val_accuracy: 0.3424
Epoch 8172/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0115 - accuracy: 1.0000 - val_loss: 7.6954 - val_accuracy: 0.3425
Epoch 8173/10000
1/1 [==============================] - 0s 117ms/step - loss: 0.0115 - accuracy: 1.0000 - val_loss: 7.6962 - val_accuracy: 0.3426
Epoch 8174/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0114 - accuracy: 1.0000 - val_loss: 7.6971 - val_accuracy: 0.3425
Epoch 8175/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0114 - accuracy: 1.0000 - val_loss: 7.6979 - val_accuracy: 0.3426
Epoch 8176/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0114 - accuracy: 1.0000 - val_loss: 7.6988 - val_accuracy: 0.3425
Epoch 8177/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0114 - accuracy: 1.0000 - val_loss: 7.6998 - val_accuracy: 0.3424
Epoch 8178/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0114 - accuracy: 1.0000 - val_loss: 7.7009 - val_accuracy: 0.3425
Epoch 8179/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0114 - accuracy: 1.0000 - val_loss: 7.7016 - val_accuracy: 0.3423
Epoch 8180/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0114 - accuracy: 1.0000 - val_loss: 7.7025 - val_accuracy: 0.3424
Epoch 8181/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0114 - accuracy: 1.0000 - val_loss: 7.7033 - val_accuracy: 0.3424
Epoch 8182/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0114 - accuracy: 1.0000 - val_loss: 7.7043 - val_accuracy: 0.3423
Epoch 8183/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0113 - accuracy: 1.0000 - val_loss: 7.7054 - val_accuracy: 0.3425
Epoch 8184/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0113 - accuracy: 1.0000 - val_loss: 7.7065 - val_accuracy: 0.3423
Epoch 8185/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0113 - accuracy: 1.0000 - val_loss: 7.7073 - val_accuracy: 0.3425
Epoch 8186/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0113 - accuracy: 1.0000 - val_loss: 7.7081 - val_accuracy: 0.3423
Epoch 8187/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0113 - accuracy: 1.0000 - val_loss: 7.7089 - val_accuracy: 0.3423
Epoch 8188/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0113 - accuracy: 1.0000 - val_loss: 7.7097 - val_accuracy: 0.3425
Epoch 8189/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0113 - accuracy: 1.0000 - val_loss: 7.7106 - val_accuracy: 0.3425
Epoch 8190/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0113 - accuracy: 1.0000 - val_loss: 7.7115 - val_accuracy: 0.3423
Epoch 8191/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0113 - accuracy: 1.0000 - val_loss: 7.7123 - val_accuracy: 0.3425
Epoch 8192/10000
1/1 [==============================] - 0s 117ms/step - loss: 0.0112 - accuracy: 1.0000 - val_loss: 7.7131 - val_accuracy: 0.3426
Epoch 8193/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0112 - accuracy: 1.0000 - val_loss: 7.7138 - val_accuracy: 0.3425
Epoch 8194/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0112 - accuracy: 1.0000 - val_loss: 7.7148 - val_accuracy: 0.3424
Epoch 8195/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0112 - accuracy: 1.0000 - val_loss: 7.7158 - val_accuracy: 0.3424
Epoch 8196/10000
1/1 [==============================] - 0s 117ms/step - loss: 0.0112 - accuracy: 1.0000 - val_loss: 7.7166 - val_accuracy: 0.3424
Epoch 8197/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0112 - accuracy: 1.0000 - val_loss: 7.7173 - val_accuracy: 0.3426
Epoch 8198/10000
1/1 [==============================] - 0s 119ms/step - loss: 0.0112 - accuracy: 1.0000 - val_loss: 7.7180 - val_accuracy: 0.3423
Epoch 8199/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0112 - accuracy: 1.0000 - val_loss: 7.7188 - val_accuracy: 0.3425
Epoch 8200/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0112 - accuracy: 1.0000 - val_loss: 7.7199 - val_accuracy: 0.3424
Epoch 8201/10000
1/1 [==============================] - 0s 118ms/step - loss: 0.0111 - accuracy: 1.0000 - val_loss: 7.7211 - val_accuracy: 0.3424
Epoch 8202/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0111 - accuracy: 1.0000 - val_loss: 7.7221 - val_accuracy: 0.3424
Epoch 8203/10000
1/1 [==============================] - 0s 117ms/step - loss: 0.0111 - accuracy: 1.0000 - val_loss: 7.7228 - val_accuracy: 0.3425
Epoch 8204/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0111 - accuracy: 1.0000 - val_loss: 7.7236 - val_accuracy: 0.3425
Epoch 8205/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0111 - accuracy: 1.0000 - val_loss: 7.7244 - val_accuracy: 0.3425
Epoch 8206/10000
1/1 [==============================] - 0s 118ms/step - loss: 0.0111 - accuracy: 1.0000 - val_loss: 7.7255 - val_accuracy: 0.3423
Epoch 8207/10000
1/1 [==============================] - 0s 122ms/step - loss: 0.0111 - accuracy: 1.0000 - val_loss: 7.7266 - val_accuracy: 0.3423
Epoch 8208/10000
1/1 [==============================] - 0s 119ms/step - loss: 0.0111 - accuracy: 1.0000 - val_loss: 7.7277 - val_accuracy: 0.3422
Epoch 8209/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0111 - accuracy: 1.0000 - val_loss: 7.7284 - val_accuracy: 0.3423
Epoch 8210/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0110 - accuracy: 1.0000 - val_loss: 7.7290 - val_accuracy: 0.3422
Epoch 8211/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0110 - accuracy: 1.0000 - val_loss: 7.7298 - val_accuracy: 0.3423
Epoch 8212/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0110 - accuracy: 1.0000 - val_loss: 7.7307 - val_accuracy: 0.3421
Epoch 8213/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0110 - accuracy: 1.0000 - val_loss: 7.7318 - val_accuracy: 0.3421
Epoch 8214/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0110 - accuracy: 1.0000 - val_loss: 7.7327 - val_accuracy: 0.3421
Epoch 8215/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0110 - accuracy: 1.0000 - val_loss: 7.7335 - val_accuracy: 0.3422
Epoch 8216/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0110 - accuracy: 1.0000 - val_loss: 7.7343 - val_accuracy: 0.3420
Epoch 8217/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0110 - accuracy: 1.0000 - val_loss: 7.7351 - val_accuracy: 0.3420
Epoch 8218/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0110 - accuracy: 1.0000 - val_loss: 7.7359 - val_accuracy: 0.3420
Epoch 8219/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0110 - accuracy: 1.0000 - val_loss: 7.7368 - val_accuracy: 0.3420
Epoch 8220/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0109 - accuracy: 1.0000 - val_loss: 7.7377 - val_accuracy: 0.3420
Epoch 8221/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0109 - accuracy: 1.0000 - val_loss: 7.7385 - val_accuracy: 0.3421
Epoch 8222/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0109 - accuracy: 1.0000 - val_loss: 7.7393 - val_accuracy: 0.3422
Epoch 8223/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0109 - accuracy: 1.0000 - val_loss: 7.7401 - val_accuracy: 0.3421
Epoch 8224/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0109 - accuracy: 1.0000 - val_loss: 7.7411 - val_accuracy: 0.3422
Epoch 8225/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0109 - accuracy: 1.0000 - val_loss: 7.7423 - val_accuracy: 0.3422
Epoch 8226/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0109 - accuracy: 1.0000 - val_loss: 7.7432 - val_accuracy: 0.3422
Epoch 8227/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0109 - accuracy: 1.0000 - val_loss: 7.7442 - val_accuracy: 0.3422
Epoch 8228/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0109 - accuracy: 1.0000 - val_loss: 7.7451 - val_accuracy: 0.3420
Epoch 8229/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0108 - accuracy: 1.0000 - val_loss: 7.7458 - val_accuracy: 0.3423
Epoch 8230/10000
1/1 [==============================] - 0s 116ms/step - loss: 0.0108 - accuracy: 1.0000 - val_loss: 7.7464 - val_accuracy: 0.3421
Epoch 8231/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0108 - accuracy: 1.0000 - val_loss: 7.7473 - val_accuracy: 0.3421
Epoch 8232/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0108 - accuracy: 1.0000 - val_loss: 7.7483 - val_accuracy: 0.3422
Epoch 8233/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0108 - accuracy: 1.0000 - val_loss: 7.7494 - val_accuracy: 0.3420
Epoch 8234/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0108 - accuracy: 1.0000 - val_loss: 7.7504 - val_accuracy: 0.3420
Epoch 8235/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0108 - accuracy: 1.0000 - val_loss: 7.7513 - val_accuracy: 0.3420
Epoch 8236/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0108 - accuracy: 1.0000 - val_loss: 7.7521 - val_accuracy: 0.3421
Epoch 8237/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0108 - accuracy: 1.0000 - val_loss: 7.7525 - val_accuracy: 0.3422
Epoch 8238/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0107 - accuracy: 1.0000 - val_loss: 7.7532 - val_accuracy: 0.3423
Epoch 8239/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0107 - accuracy: 1.0000 - val_loss: 7.7541 - val_accuracy: 0.3422
Epoch 8240/10000
1/1 [==============================] - 0s 118ms/step - loss: 0.0107 - accuracy: 1.0000 - val_loss: 7.7551 - val_accuracy: 0.3421
Epoch 8241/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0107 - accuracy: 1.0000 - val_loss: 7.7564 - val_accuracy: 0.3421
Epoch 8242/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0107 - accuracy: 1.0000 - val_loss: 7.7574 - val_accuracy: 0.3422
Epoch 8243/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0107 - accuracy: 1.0000 - val_loss: 7.7582 - val_accuracy: 0.3421
Epoch 8244/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0107 - accuracy: 1.0000 - val_loss: 7.7588 - val_accuracy: 0.3422
Epoch 8245/10000
1/1 [==============================] - 0s 116ms/step - loss: 0.0107 - accuracy: 1.0000 - val_loss: 7.7595 - val_accuracy: 0.3421
Epoch 8246/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0107 - accuracy: 1.0000 - val_loss: 7.7604 - val_accuracy: 0.3422
Epoch 8247/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0107 - accuracy: 1.0000 - val_loss: 7.7615 - val_accuracy: 0.3424
Epoch 8248/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0106 - accuracy: 1.0000 - val_loss: 7.7626 - val_accuracy: 0.3422
Epoch 8249/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0106 - accuracy: 1.0000 - val_loss: 7.7635 - val_accuracy: 0.3421
Epoch 8250/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0106 - accuracy: 1.0000 - val_loss: 7.7644 - val_accuracy: 0.3422
Epoch 8251/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0106 - accuracy: 1.0000 - val_loss: 7.7650 - val_accuracy: 0.3423
Epoch 8252/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0106 - accuracy: 1.0000 - val_loss: 7.7657 - val_accuracy: 0.3422
Epoch 8253/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0106 - accuracy: 1.0000 - val_loss: 7.7665 - val_accuracy: 0.3422
Epoch 8254/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0106 - accuracy: 1.0000 - val_loss: 7.7673 - val_accuracy: 0.3423
Epoch 8255/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0106 - accuracy: 1.0000 - val_loss: 7.7684 - val_accuracy: 0.3422
Epoch 8256/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0106 - accuracy: 1.0000 - val_loss: 7.7693 - val_accuracy: 0.3422
Epoch 8257/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0105 - accuracy: 1.0000 - val_loss: 7.7702 - val_accuracy: 0.3422
Epoch 8258/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0105 - accuracy: 1.0000 - val_loss: 7.7710 - val_accuracy: 0.3422
Epoch 8259/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0105 - accuracy: 1.0000 - val_loss: 7.7719 - val_accuracy: 0.3422
Epoch 8260/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0105 - accuracy: 1.0000 - val_loss: 7.7727 - val_accuracy: 0.3422
Epoch 8261/10000
1/1 [==============================] - 0s 117ms/step - loss: 0.0105 - accuracy: 1.0000 - val_loss: 7.7736 - val_accuracy: 0.3423
Epoch 8262/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0105 - accuracy: 1.0000 - val_loss: 7.7746 - val_accuracy: 0.3423
Epoch 8263/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0105 - accuracy: 1.0000 - val_loss: 7.7756 - val_accuracy: 0.3423
Epoch 8264/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0105 - accuracy: 1.0000 - val_loss: 7.7766 - val_accuracy: 0.3423
Epoch 8265/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0105 - accuracy: 1.0000 - val_loss: 7.7776 - val_accuracy: 0.3422
Epoch 8266/10000
1/1 [==============================] - 0s 117ms/step - loss: 0.0105 - accuracy: 1.0000 - val_loss: 7.7784 - val_accuracy: 0.3421
Epoch 8267/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0104 - accuracy: 1.0000 - val_loss: 7.7791 - val_accuracy: 0.3420
Epoch 8268/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0104 - accuracy: 1.0000 - val_loss: 7.7798 - val_accuracy: 0.3420
Epoch 8269/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0104 - accuracy: 1.0000 - val_loss: 7.7804 - val_accuracy: 0.3423
Epoch 8270/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0104 - accuracy: 1.0000 - val_loss: 7.7811 - val_accuracy: 0.3421
Epoch 8271/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0104 - accuracy: 1.0000 - val_loss: 7.7822 - val_accuracy: 0.3421
Epoch 8272/10000
1/1 [==============================] - 0s 116ms/step - loss: 0.0104 - accuracy: 1.0000 - val_loss: 7.7834 - val_accuracy: 0.3422
Epoch 8273/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0104 - accuracy: 1.0000 - val_loss: 7.7843 - val_accuracy: 0.3422
Epoch 8274/10000
1/1 [==============================] - 0s 116ms/step - loss: 0.0104 - accuracy: 1.0000 - val_loss: 7.7853 - val_accuracy: 0.3422
Epoch 8275/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0104 - accuracy: 1.0000 - val_loss: 7.7860 - val_accuracy: 0.3421
Epoch 8276/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0104 - accuracy: 1.0000 - val_loss: 7.7867 - val_accuracy: 0.3422
Epoch 8277/10000
1/1 [==============================] - 0s 118ms/step - loss: 0.0103 - accuracy: 1.0000 - val_loss: 7.7875 - val_accuracy: 0.3420
Epoch 8278/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0103 - accuracy: 1.0000 - val_loss: 7.7883 - val_accuracy: 0.3420
Epoch 8279/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0103 - accuracy: 1.0000 - val_loss: 7.7891 - val_accuracy: 0.3422
Epoch 8280/10000
1/1 [==============================] - 0s 119ms/step - loss: 0.0103 - accuracy: 1.0000 - val_loss: 7.7900 - val_accuracy: 0.3421
Epoch 8281/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0103 - accuracy: 1.0000 - val_loss: 7.7909 - val_accuracy: 0.3423
Epoch 8282/10000
1/1 [==============================] - 0s 118ms/step - loss: 0.0103 - accuracy: 1.0000 - val_loss: 7.7919 - val_accuracy: 0.3424
Epoch 8283/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0103 - accuracy: 1.0000 - val_loss: 7.7928 - val_accuracy: 0.3420
Epoch 8284/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0103 - accuracy: 1.0000 - val_loss: 7.7937 - val_accuracy: 0.3422
Epoch 8285/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0103 - accuracy: 1.0000 - val_loss: 7.7942 - val_accuracy: 0.3422
Epoch 8286/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0103 - accuracy: 1.0000 - val_loss: 7.7950 - val_accuracy: 0.3421
Epoch 8287/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0102 - accuracy: 1.0000 - val_loss: 7.7959 - val_accuracy: 0.3422
Epoch 8288/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0102 - accuracy: 1.0000 - val_loss: 7.7969 - val_accuracy: 0.3422
Epoch 8289/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0102 - accuracy: 1.0000 - val_loss: 7.7978 - val_accuracy: 0.3421
Epoch 8290/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0102 - accuracy: 1.0000 - val_loss: 7.7988 - val_accuracy: 0.3423
Epoch 8291/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0102 - accuracy: 1.0000 - val_loss: 7.7997 - val_accuracy: 0.3423
Epoch 8292/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0102 - accuracy: 1.0000 - val_loss: 7.8005 - val_accuracy: 0.3422
Epoch 8293/10000
1/1 [==============================] - 0s 104ms/step - loss: 0.0102 - accuracy: 1.0000 - val_loss: 7.8014 - val_accuracy: 0.3423
Epoch 8294/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0102 - accuracy: 1.0000 - val_loss: 7.8023 - val_accuracy: 0.3423
Epoch 8295/10000
1/1 [==============================] - 0s 117ms/step - loss: 0.0102 - accuracy: 1.0000 - val_loss: 7.8031 - val_accuracy: 0.3423
Epoch 8296/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0102 - accuracy: 1.0000 - val_loss: 7.8037 - val_accuracy: 0.3423
Epoch 8297/10000
1/1 [==============================] - 0s 104ms/step - loss: 0.0101 - accuracy: 1.0000 - val_loss: 7.8043 - val_accuracy: 0.3423
Epoch 8298/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0101 - accuracy: 1.0000 - val_loss: 7.8054 - val_accuracy: 0.3423
Epoch 8299/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0101 - accuracy: 1.0000 - val_loss: 7.8064 - val_accuracy: 0.3423
Epoch 8300/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0101 - accuracy: 1.0000 - val_loss: 7.8075 - val_accuracy: 0.3423
Epoch 8301/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0101 - accuracy: 1.0000 - val_loss: 7.8085 - val_accuracy: 0.3424
Epoch 8302/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0101 - accuracy: 1.0000 - val_loss: 7.8092 - val_accuracy: 0.3425
Epoch 8303/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0101 - accuracy: 1.0000 - val_loss: 7.8099 - val_accuracy: 0.3426
Epoch 8304/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0101 - accuracy: 1.0000 - val_loss: 7.8107 - val_accuracy: 0.3425
Epoch 8305/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0101 - accuracy: 1.0000 - val_loss: 7.8116 - val_accuracy: 0.3423
Epoch 8306/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0101 - accuracy: 1.0000 - val_loss: 7.8124 - val_accuracy: 0.3426
Epoch 8307/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0100 - accuracy: 1.0000 - val_loss: 7.8132 - val_accuracy: 0.3423
Epoch 8308/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0100 - accuracy: 1.0000 - val_loss: 7.8141 - val_accuracy: 0.3425
Epoch 8309/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0100 - accuracy: 1.0000 - val_loss: 7.8150 - val_accuracy: 0.3424
Epoch 8310/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0100 - accuracy: 1.0000 - val_loss: 7.8160 - val_accuracy: 0.3425
Epoch 8311/10000
1/1 [==============================] - 0s 104ms/step - loss: 0.0100 - accuracy: 1.0000 - val_loss: 7.8170 - val_accuracy: 0.3425
Epoch 8312/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0100 - accuracy: 1.0000 - val_loss: 7.8179 - val_accuracy: 0.3425
Epoch 8313/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0100 - accuracy: 1.0000 - val_loss: 7.8187 - val_accuracy: 0.3426
Epoch 8314/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0100 - accuracy: 1.0000 - val_loss: 7.8195 - val_accuracy: 0.3426
Epoch 8315/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0100 - accuracy: 1.0000 - val_loss: 7.8200 - val_accuracy: 0.3425
Epoch 8316/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0100 - accuracy: 1.0000 - val_loss: 7.8208 - val_accuracy: 0.3427
Epoch 8317/10000
1/1 [==============================] - 0s 104ms/step - loss: 0.0100 - accuracy: 1.0000 - val_loss: 7.8218 - val_accuracy: 0.3427
Epoch 8318/10000
1/1 [==============================] - 0s 104ms/step - loss: 0.0099 - accuracy: 1.0000 - val_loss: 7.8228 - val_accuracy: 0.3427
Epoch 8319/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0099 - accuracy: 1.0000 - val_loss: 7.8239 - val_accuracy: 0.3428
Epoch 8320/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0099 - accuracy: 1.0000 - val_loss: 7.8248 - val_accuracy: 0.3429
Epoch 8321/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0099 - accuracy: 1.0000 - val_loss: 7.8256 - val_accuracy: 0.3427
Epoch 8322/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0099 - accuracy: 1.0000 - val_loss: 7.8264 - val_accuracy: 0.3428
Epoch 8323/10000
1/1 [==============================] - 0s 122ms/step - loss: 0.0099 - accuracy: 1.0000 - val_loss: 7.8273 - val_accuracy: 0.3428
Epoch 8324/10000
1/1 [==============================] - 0s 117ms/step - loss: 0.0099 - accuracy: 1.0000 - val_loss: 7.8282 - val_accuracy: 0.3429
Epoch 8325/10000
1/1 [==============================] - 0s 119ms/step - loss: 0.0099 - accuracy: 1.0000 - val_loss: 7.8290 - val_accuracy: 0.3429
Epoch 8326/10000
1/1 [==============================] - 0s 116ms/step - loss: 0.0099 - accuracy: 1.0000 - val_loss: 7.8297 - val_accuracy: 0.3430
Epoch 8327/10000
1/1 [==============================] - 0s 126ms/step - loss: 0.0099 - accuracy: 1.0000 - val_loss: 7.8303 - val_accuracy: 0.3428
Epoch 8328/10000
1/1 [==============================] - 0s 119ms/step - loss: 0.0098 - accuracy: 1.0000 - val_loss: 7.8311 - val_accuracy: 0.3429
Epoch 8329/10000
1/1 [==============================] - 0s 120ms/step - loss: 0.0098 - accuracy: 1.0000 - val_loss: 7.8321 - val_accuracy: 0.3430
Epoch 8330/10000
1/1 [==============================] - 0s 119ms/step - loss: 0.0098 - accuracy: 1.0000 - val_loss: 7.8332 - val_accuracy: 0.3429
Epoch 8331/10000
1/1 [==============================] - 0s 119ms/step - loss: 0.0098 - accuracy: 1.0000 - val_loss: 7.8342 - val_accuracy: 0.3431
Epoch 8332/10000
1/1 [==============================] - 0s 125ms/step - loss: 0.0098 - accuracy: 1.0000 - val_loss: 7.8351 - val_accuracy: 0.3429
Epoch 8333/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0098 - accuracy: 1.0000 - val_loss: 7.8356 - val_accuracy: 0.3430
Epoch 8334/10000
1/1 [==============================] - 0s 120ms/step - loss: 0.0098 - accuracy: 1.0000 - val_loss: 7.8361 - val_accuracy: 0.3430
Epoch 8335/10000
1/1 [==============================] - 0s 120ms/step - loss: 0.0098 - accuracy: 1.0000 - val_loss: 7.8369 - val_accuracy: 0.3429
Epoch 8336/10000
1/1 [==============================] - 0s 122ms/step - loss: 0.0098 - accuracy: 1.0000 - val_loss: 7.8379 - val_accuracy: 0.3431
Epoch 8337/10000
1/1 [==============================] - 0s 124ms/step - loss: 0.0098 - accuracy: 1.0000 - val_loss: 7.8389 - val_accuracy: 0.3428
Epoch 8338/10000
1/1 [==============================] - 0s 121ms/step - loss: 0.0098 - accuracy: 1.0000 - val_loss: 7.8399 - val_accuracy: 0.3429
Epoch 8339/10000
1/1 [==============================] - 0s 116ms/step - loss: 0.0097 - accuracy: 1.0000 - val_loss: 7.8406 - val_accuracy: 0.3428
Epoch 8340/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0097 - accuracy: 1.0000 - val_loss: 7.8414 - val_accuracy: 0.3430
Epoch 8341/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0097 - accuracy: 1.0000 - val_loss: 7.8422 - val_accuracy: 0.3429
Epoch 8342/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0097 - accuracy: 1.0000 - val_loss: 7.8432 - val_accuracy: 0.3431
Epoch 8343/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0097 - accuracy: 1.0000 - val_loss: 7.8443 - val_accuracy: 0.3431
Epoch 8344/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0097 - accuracy: 1.0000 - val_loss: 7.8453 - val_accuracy: 0.3429
Epoch 8345/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0097 - accuracy: 1.0000 - val_loss: 7.8462 - val_accuracy: 0.3428
Epoch 8346/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0097 - accuracy: 1.0000 - val_loss: 7.8471 - val_accuracy: 0.3429
Epoch 8347/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0097 - accuracy: 1.0000 - val_loss: 7.8478 - val_accuracy: 0.3433
Epoch 8348/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0097 - accuracy: 1.0000 - val_loss: 7.8484 - val_accuracy: 0.3430
Epoch 8349/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0096 - accuracy: 1.0000 - val_loss: 7.8492 - val_accuracy: 0.3429
Epoch 8350/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0096 - accuracy: 1.0000 - val_loss: 7.8502 - val_accuracy: 0.3430
Epoch 8351/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0096 - accuracy: 1.0000 - val_loss: 7.8513 - val_accuracy: 0.3429
Epoch 8352/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0096 - accuracy: 1.0000 - val_loss: 7.8522 - val_accuracy: 0.3431
Epoch 8353/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0096 - accuracy: 1.0000 - val_loss: 7.8529 - val_accuracy: 0.3429
Epoch 8354/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0096 - accuracy: 1.0000 - val_loss: 7.8535 - val_accuracy: 0.3430
Epoch 8355/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0096 - accuracy: 1.0000 - val_loss: 7.8545 - val_accuracy: 0.3431
Epoch 8356/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0096 - accuracy: 1.0000 - val_loss: 7.8554 - val_accuracy: 0.3432
Epoch 8357/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0096 - accuracy: 1.0000 - val_loss: 7.8564 - val_accuracy: 0.3430
Epoch 8358/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0096 - accuracy: 1.0000 - val_loss: 7.8573 - val_accuracy: 0.3431
Epoch 8359/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0096 - accuracy: 1.0000 - val_loss: 7.8579 - val_accuracy: 0.3430
Epoch 8360/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0095 - accuracy: 1.0000 - val_loss: 7.8586 - val_accuracy: 0.3430
Epoch 8361/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0095 - accuracy: 1.0000 - val_loss: 7.8593 - val_accuracy: 0.3429
Epoch 8362/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0095 - accuracy: 1.0000 - val_loss: 7.8601 - val_accuracy: 0.3431
Epoch 8363/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0095 - accuracy: 1.0000 - val_loss: 7.8611 - val_accuracy: 0.3429
Epoch 8364/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0095 - accuracy: 1.0000 - val_loss: 7.8619 - val_accuracy: 0.3429
Epoch 8365/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0095 - accuracy: 1.0000 - val_loss: 7.8629 - val_accuracy: 0.3431
Epoch 8366/10000
1/1 [==============================] - 0s 121ms/step - loss: 0.0095 - accuracy: 1.0000 - val_loss: 7.8638 - val_accuracy: 0.3429
Epoch 8367/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0095 - accuracy: 1.0000 - val_loss: 7.8647 - val_accuracy: 0.3428
Epoch 8368/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0095 - accuracy: 1.0000 - val_loss: 7.8654 - val_accuracy: 0.3430
Epoch 8369/10000
1/1 [==============================] - 0s 120ms/step - loss: 0.0095 - accuracy: 1.0000 - val_loss: 7.8661 - val_accuracy: 0.3428
Epoch 8370/10000
1/1 [==============================] - 0s 122ms/step - loss: 0.0095 - accuracy: 1.0000 - val_loss: 7.8670 - val_accuracy: 0.3429
Epoch 8371/10000
1/1 [==============================] - 0s 118ms/step - loss: 0.0094 - accuracy: 1.0000 - val_loss: 7.8679 - val_accuracy: 0.3429
Epoch 8372/10000
1/1 [==============================] - 0s 122ms/step - loss: 0.0094 - accuracy: 1.0000 - val_loss: 7.8687 - val_accuracy: 0.3429
Epoch 8373/10000
1/1 [==============================] - 0s 116ms/step - loss: 0.0094 - accuracy: 1.0000 - val_loss: 7.8695 - val_accuracy: 0.3429
Epoch 8374/10000
1/1 [==============================] - 0s 116ms/step - loss: 0.0094 - accuracy: 1.0000 - val_loss: 7.8703 - val_accuracy: 0.3429
Epoch 8375/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0094 - accuracy: 1.0000 - val_loss: 7.8711 - val_accuracy: 0.3429
Epoch 8376/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0094 - accuracy: 1.0000 - val_loss: 7.8721 - val_accuracy: 0.3429
Epoch 8377/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0094 - accuracy: 1.0000 - val_loss: 7.8728 - val_accuracy: 0.3429
Epoch 8378/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0094 - accuracy: 1.0000 - val_loss: 7.8736 - val_accuracy: 0.3429
Epoch 8379/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0094 - accuracy: 1.0000 - val_loss: 7.8746 - val_accuracy: 0.3429
Epoch 8380/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0094 - accuracy: 1.0000 - val_loss: 7.8756 - val_accuracy: 0.3428
Epoch 8381/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0094 - accuracy: 1.0000 - val_loss: 7.8765 - val_accuracy: 0.3429
Epoch 8382/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0093 - accuracy: 1.0000 - val_loss: 7.8773 - val_accuracy: 0.3429
Epoch 8383/10000
1/1 [==============================] - 0s 124ms/step - loss: 0.0093 - accuracy: 1.0000 - val_loss: 7.8781 - val_accuracy: 0.3429
Epoch 8384/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0093 - accuracy: 1.0000 - val_loss: 7.8788 - val_accuracy: 0.3429
Epoch 8385/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0093 - accuracy: 1.0000 - val_loss: 7.8797 - val_accuracy: 0.3429
Epoch 8386/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0093 - accuracy: 1.0000 - val_loss: 7.8808 - val_accuracy: 0.3429
Epoch 8387/10000
1/1 [==============================] - 0s 104ms/step - loss: 0.0093 - accuracy: 1.0000 - val_loss: 7.8817 - val_accuracy: 0.3430
Epoch 8388/10000
1/1 [==============================] - 0s 104ms/step - loss: 0.0093 - accuracy: 1.0000 - val_loss: 7.8825 - val_accuracy: 0.3430
Epoch 8389/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0093 - accuracy: 1.0000 - val_loss: 7.8831 - val_accuracy: 0.3430
Epoch 8390/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0093 - accuracy: 1.0000 - val_loss: 7.8837 - val_accuracy: 0.3429
Epoch 8391/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0093 - accuracy: 1.0000 - val_loss: 7.8845 - val_accuracy: 0.3431
Epoch 8392/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0093 - accuracy: 1.0000 - val_loss: 7.8853 - val_accuracy: 0.3430
Epoch 8393/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0092 - accuracy: 1.0000 - val_loss: 7.8862 - val_accuracy: 0.3431
Epoch 8394/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0092 - accuracy: 1.0000 - val_loss: 7.8871 - val_accuracy: 0.3433
Epoch 8395/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0092 - accuracy: 1.0000 - val_loss: 7.8878 - val_accuracy: 0.3429
Epoch 8396/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0092 - accuracy: 1.0000 - val_loss: 7.8883 - val_accuracy: 0.3431
Epoch 8397/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0092 - accuracy: 1.0000 - val_loss: 7.8891 - val_accuracy: 0.3431
Epoch 8398/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0092 - accuracy: 1.0000 - val_loss: 7.8900 - val_accuracy: 0.3432
Epoch 8399/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0092 - accuracy: 1.0000 - val_loss: 7.8912 - val_accuracy: 0.3430
Epoch 8400/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0092 - accuracy: 1.0000 - val_loss: 7.8923 - val_accuracy: 0.3431
Epoch 8401/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0092 - accuracy: 1.0000 - val_loss: 7.8933 - val_accuracy: 0.3431
Epoch 8402/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0092 - accuracy: 1.0000 - val_loss: 7.8941 - val_accuracy: 0.3431
Epoch 8403/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0092 - accuracy: 1.0000 - val_loss: 7.8947 - val_accuracy: 0.3431
Epoch 8404/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0092 - accuracy: 1.0000 - val_loss: 7.8953 - val_accuracy: 0.3432
Epoch 8405/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0091 - accuracy: 1.0000 - val_loss: 7.8960 - val_accuracy: 0.3431
Epoch 8406/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0091 - accuracy: 1.0000 - val_loss: 7.8971 - val_accuracy: 0.3432
Epoch 8407/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0091 - accuracy: 1.0000 - val_loss: 7.8981 - val_accuracy: 0.3432
Epoch 8408/10000
1/1 [==============================] - 0s 118ms/step - loss: 0.0091 - accuracy: 1.0000 - val_loss: 7.8990 - val_accuracy: 0.3432
Epoch 8409/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0091 - accuracy: 1.0000 - val_loss: 7.8997 - val_accuracy: 0.3432
Epoch 8410/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0091 - accuracy: 1.0000 - val_loss: 7.9003 - val_accuracy: 0.3432
Epoch 8411/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0091 - accuracy: 1.0000 - val_loss: 7.9010 - val_accuracy: 0.3433
Epoch 8412/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0091 - accuracy: 1.0000 - val_loss: 7.9019 - val_accuracy: 0.3431
Epoch 8413/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0091 - accuracy: 1.0000 - val_loss: 7.9029 - val_accuracy: 0.3431
Epoch 8414/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0091 - accuracy: 1.0000 - val_loss: 7.9039 - val_accuracy: 0.3433
Epoch 8415/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0091 - accuracy: 1.0000 - val_loss: 7.9049 - val_accuracy: 0.3433
Epoch 8416/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0091 - accuracy: 1.0000 - val_loss: 7.9057 - val_accuracy: 0.3433
Epoch 8417/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0090 - accuracy: 1.0000 - val_loss: 7.9065 - val_accuracy: 0.3432
Epoch 8418/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0090 - accuracy: 1.0000 - val_loss: 7.9073 - val_accuracy: 0.3433
Epoch 8419/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0090 - accuracy: 1.0000 - val_loss: 7.9082 - val_accuracy: 0.3433
Epoch 8420/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0090 - accuracy: 1.0000 - val_loss: 7.9091 - val_accuracy: 0.3432
Epoch 8421/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0090 - accuracy: 1.0000 - val_loss: 7.9099 - val_accuracy: 0.3431
Epoch 8422/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0090 - accuracy: 1.0000 - val_loss: 7.9107 - val_accuracy: 0.3432
Epoch 8423/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0090 - accuracy: 1.0000 - val_loss: 7.9115 - val_accuracy: 0.3432
Epoch 8424/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0090 - accuracy: 1.0000 - val_loss: 7.9122 - val_accuracy: 0.3433
Epoch 8425/10000
1/1 [==============================] - 0s 117ms/step - loss: 0.0090 - accuracy: 1.0000 - val_loss: 7.9132 - val_accuracy: 0.3432
Epoch 8426/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0090 - accuracy: 1.0000 - val_loss: 7.9141 - val_accuracy: 0.3432
Epoch 8427/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0090 - accuracy: 1.0000 - val_loss: 7.9150 - val_accuracy: 0.3432
Epoch 8428/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0089 - accuracy: 1.0000 - val_loss: 7.9156 - val_accuracy: 0.3432
Epoch 8429/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0089 - accuracy: 1.0000 - val_loss: 7.9161 - val_accuracy: 0.3432
Epoch 8430/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0089 - accuracy: 1.0000 - val_loss: 7.9168 - val_accuracy: 0.3432
Epoch 8431/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0089 - accuracy: 1.0000 - val_loss: 7.9179 - val_accuracy: 0.3432
Epoch 8432/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0089 - accuracy: 1.0000 - val_loss: 7.9189 - val_accuracy: 0.3432
Epoch 8433/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0089 - accuracy: 1.0000 - val_loss: 7.9201 - val_accuracy: 0.3433
Epoch 8434/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0089 - accuracy: 1.0000 - val_loss: 7.9210 - val_accuracy: 0.3433
Epoch 8435/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0089 - accuracy: 1.0000 - val_loss: 7.9219 - val_accuracy: 0.3433
Epoch 8436/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0089 - accuracy: 1.0000 - val_loss: 7.9223 - val_accuracy: 0.3433
Epoch 8437/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0089 - accuracy: 1.0000 - val_loss: 7.9229 - val_accuracy: 0.3432
Epoch 8438/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0089 - accuracy: 1.0000 - val_loss: 7.9236 - val_accuracy: 0.3432
Epoch 8439/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0089 - accuracy: 1.0000 - val_loss: 7.9245 - val_accuracy: 0.3432
Epoch 8440/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0088 - accuracy: 1.0000 - val_loss: 7.9255 - val_accuracy: 0.3432
Epoch 8441/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0088 - accuracy: 1.0000 - val_loss: 7.9266 - val_accuracy: 0.3433
Epoch 8442/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0088 - accuracy: 1.0000 - val_loss: 7.9274 - val_accuracy: 0.3432
Epoch 8443/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0088 - accuracy: 1.0000 - val_loss: 7.9280 - val_accuracy: 0.3432
Epoch 8444/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0088 - accuracy: 1.0000 - val_loss: 7.9287 - val_accuracy: 0.3432
Epoch 8445/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0088 - accuracy: 1.0000 - val_loss: 7.9293 - val_accuracy: 0.3432
Epoch 8446/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0088 - accuracy: 1.0000 - val_loss: 7.9303 - val_accuracy: 0.3432
Epoch 8447/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0088 - accuracy: 1.0000 - val_loss: 7.9313 - val_accuracy: 0.3432
Epoch 8448/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0088 - accuracy: 1.0000 - val_loss: 7.9325 - val_accuracy: 0.3431
Epoch 8449/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0088 - accuracy: 1.0000 - val_loss: 7.9333 - val_accuracy: 0.3432
Epoch 8450/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0088 - accuracy: 1.0000 - val_loss: 7.9340 - val_accuracy: 0.3432
Epoch 8451/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0088 - accuracy: 1.0000 - val_loss: 7.9346 - val_accuracy: 0.3432
Epoch 8452/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0087 - accuracy: 1.0000 - val_loss: 7.9353 - val_accuracy: 0.3432
Epoch 8453/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0087 - accuracy: 1.0000 - val_loss: 7.9361 - val_accuracy: 0.3432
Epoch 8454/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0087 - accuracy: 1.0000 - val_loss: 7.9371 - val_accuracy: 0.3432
Epoch 8455/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0087 - accuracy: 1.0000 - val_loss: 7.9380 - val_accuracy: 0.3432
Epoch 8456/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0087 - accuracy: 1.0000 - val_loss: 7.9389 - val_accuracy: 0.3432
Epoch 8457/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0087 - accuracy: 1.0000 - val_loss: 7.9397 - val_accuracy: 0.3431
Epoch 8458/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0087 - accuracy: 1.0000 - val_loss: 7.9403 - val_accuracy: 0.3432
Epoch 8459/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0087 - accuracy: 1.0000 - val_loss: 7.9411 - val_accuracy: 0.3432
Epoch 8460/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0087 - accuracy: 1.0000 - val_loss: 7.9418 - val_accuracy: 0.3432
Epoch 8461/10000
1/1 [==============================] - 0s 118ms/step - loss: 0.0087 - accuracy: 1.0000 - val_loss: 7.9427 - val_accuracy: 0.3432
Epoch 8462/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0087 - accuracy: 1.0000 - val_loss: 7.9438 - val_accuracy: 0.3432
Epoch 8463/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0087 - accuracy: 1.0000 - val_loss: 7.9449 - val_accuracy: 0.3432
Epoch 8464/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0087 - accuracy: 1.0000 - val_loss: 7.9457 - val_accuracy: 0.3432
Epoch 8465/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0086 - accuracy: 1.0000 - val_loss: 7.9466 - val_accuracy: 0.3431
Epoch 8466/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0086 - accuracy: 1.0000 - val_loss: 7.9472 - val_accuracy: 0.3431
Epoch 8467/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0086 - accuracy: 1.0000 - val_loss: 7.9479 - val_accuracy: 0.3432
Epoch 8468/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0086 - accuracy: 1.0000 - val_loss: 7.9486 - val_accuracy: 0.3431
Epoch 8469/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0086 - accuracy: 1.0000 - val_loss: 7.9493 - val_accuracy: 0.3432
Epoch 8470/10000
1/1 [==============================] - 0s 103ms/step - loss: 0.0086 - accuracy: 1.0000 - val_loss: 7.9503 - val_accuracy: 0.3431
Epoch 8471/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0086 - accuracy: 1.0000 - val_loss: 7.9512 - val_accuracy: 0.3432
Epoch 8472/10000
1/1 [==============================] - 0s 116ms/step - loss: 0.0086 - accuracy: 1.0000 - val_loss: 7.9522 - val_accuracy: 0.3431
Epoch 8473/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0086 - accuracy: 1.0000 - val_loss: 7.9531 - val_accuracy: 0.3432
Epoch 8474/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0086 - accuracy: 1.0000 - val_loss: 7.9538 - val_accuracy: 0.3431
Epoch 8475/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0086 - accuracy: 1.0000 - val_loss: 7.9545 - val_accuracy: 0.3431
Epoch 8476/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0086 - accuracy: 1.0000 - val_loss: 7.9555 - val_accuracy: 0.3432
Epoch 8477/10000
1/1 [==============================] - 0s 125ms/step - loss: 0.0085 - accuracy: 1.0000 - val_loss: 7.9565 - val_accuracy: 0.3430
Epoch 8478/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0085 - accuracy: 1.0000 - val_loss: 7.9574 - val_accuracy: 0.3431
Epoch 8479/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0085 - accuracy: 1.0000 - val_loss: 7.9580 - val_accuracy: 0.3431
Epoch 8480/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0085 - accuracy: 1.0000 - val_loss: 7.9585 - val_accuracy: 0.3430
Epoch 8481/10000
1/1 [==============================] - 0s 118ms/step - loss: 0.0085 - accuracy: 1.0000 - val_loss: 7.9592 - val_accuracy: 0.3430
Epoch 8482/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0085 - accuracy: 1.0000 - val_loss: 7.9600 - val_accuracy: 0.3430
Epoch 8483/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0085 - accuracy: 1.0000 - val_loss: 7.9610 - val_accuracy: 0.3431
Epoch 8484/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0085 - accuracy: 1.0000 - val_loss: 7.9620 - val_accuracy: 0.3430
Epoch 8485/10000
1/1 [==============================] - 0s 120ms/step - loss: 0.0085 - accuracy: 1.0000 - val_loss: 7.9630 - val_accuracy: 0.3431
Epoch 8486/10000
1/1 [==============================] - 0s 117ms/step - loss: 0.0085 - accuracy: 1.0000 - val_loss: 7.9638 - val_accuracy: 0.3432
Epoch 8487/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0085 - accuracy: 1.0000 - val_loss: 7.9644 - val_accuracy: 0.3430
Epoch 8488/10000
1/1 [==============================] - 0s 116ms/step - loss: 0.0085 - accuracy: 1.0000 - val_loss: 7.9650 - val_accuracy: 0.3429
Epoch 8489/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0085 - accuracy: 1.0000 - val_loss: 7.9656 - val_accuracy: 0.3429
Epoch 8490/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0084 - accuracy: 1.0000 - val_loss: 7.9664 - val_accuracy: 0.3430
Epoch 8491/10000
1/1 [==============================] - 0s 103ms/step - loss: 0.0084 - accuracy: 1.0000 - val_loss: 7.9675 - val_accuracy: 0.3429
Epoch 8492/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0084 - accuracy: 1.0000 - val_loss: 7.9686 - val_accuracy: 0.3431
Epoch 8493/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0084 - accuracy: 1.0000 - val_loss: 7.9695 - val_accuracy: 0.3430
Epoch 8494/10000
1/1 [==============================] - 0s 116ms/step - loss: 0.0084 - accuracy: 1.0000 - val_loss: 7.9703 - val_accuracy: 0.3430
Epoch 8495/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0084 - accuracy: 1.0000 - val_loss: 7.9709 - val_accuracy: 0.3430
Epoch 8496/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0084 - accuracy: 1.0000 - val_loss: 7.9716 - val_accuracy: 0.3430
Epoch 8497/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0084 - accuracy: 1.0000 - val_loss: 7.9725 - val_accuracy: 0.3430
Epoch 8498/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0084 - accuracy: 1.0000 - val_loss: 7.9734 - val_accuracy: 0.3431
Epoch 8499/10000
1/1 [==============================] - 0s 119ms/step - loss: 0.0084 - accuracy: 1.0000 - val_loss: 7.9743 - val_accuracy: 0.3429
Epoch 8500/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0084 - accuracy: 1.0000 - val_loss: 7.9751 - val_accuracy: 0.3431
Epoch 8501/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0084 - accuracy: 1.0000 - val_loss: 7.9757 - val_accuracy: 0.3430
Epoch 8502/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0083 - accuracy: 1.0000 - val_loss: 7.9764 - val_accuracy: 0.3429
Epoch 8503/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0083 - accuracy: 1.0000 - val_loss: 7.9772 - val_accuracy: 0.3430
Epoch 8504/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0083 - accuracy: 1.0000 - val_loss: 7.9781 - val_accuracy: 0.3430
Epoch 8505/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0083 - accuracy: 1.0000 - val_loss: 7.9790 - val_accuracy: 0.3429
Epoch 8506/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0083 - accuracy: 1.0000 - val_loss: 7.9799 - val_accuracy: 0.3430
Epoch 8507/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0083 - accuracy: 1.0000 - val_loss: 7.9809 - val_accuracy: 0.3430
Epoch 8508/10000
1/1 [==============================] - 0s 103ms/step - loss: 0.0083 - accuracy: 1.0000 - val_loss: 7.9818 - val_accuracy: 0.3430
Epoch 8509/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0083 - accuracy: 1.0000 - val_loss: 7.9825 - val_accuracy: 0.3430
Epoch 8510/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0083 - accuracy: 1.0000 - val_loss: 7.9831 - val_accuracy: 0.3431
Epoch 8511/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0083 - accuracy: 1.0000 - val_loss: 7.9839 - val_accuracy: 0.3431
Epoch 8512/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0083 - accuracy: 1.0000 - val_loss: 7.9847 - val_accuracy: 0.3430
Epoch 8513/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0083 - accuracy: 1.0000 - val_loss: 7.9855 - val_accuracy: 0.3430
Epoch 8514/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0083 - accuracy: 1.0000 - val_loss: 7.9864 - val_accuracy: 0.3430
Epoch 8515/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0083 - accuracy: 1.0000 - val_loss: 7.9869 - val_accuracy: 0.3430
Epoch 8516/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0082 - accuracy: 1.0000 - val_loss: 7.9877 - val_accuracy: 0.3431
Epoch 8517/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0082 - accuracy: 1.0000 - val_loss: 7.9885 - val_accuracy: 0.3431
Epoch 8518/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0082 - accuracy: 1.0000 - val_loss: 7.9895 - val_accuracy: 0.3431
Epoch 8519/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0082 - accuracy: 1.0000 - val_loss: 7.9904 - val_accuracy: 0.3431
Epoch 8520/10000
1/1 [==============================] - 0s 122ms/step - loss: 0.0082 - accuracy: 1.0000 - val_loss: 7.9913 - val_accuracy: 0.3429
Epoch 8521/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0082 - accuracy: 1.0000 - val_loss: 7.9919 - val_accuracy: 0.3430
Epoch 8522/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0082 - accuracy: 1.0000 - val_loss: 7.9926 - val_accuracy: 0.3430
Epoch 8523/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0082 - accuracy: 1.0000 - val_loss: 7.9935 - val_accuracy: 0.3430
Epoch 8524/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0082 - accuracy: 1.0000 - val_loss: 7.9945 - val_accuracy: 0.3430
Epoch 8525/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0082 - accuracy: 1.0000 - val_loss: 7.9955 - val_accuracy: 0.3430
Epoch 8526/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0082 - accuracy: 1.0000 - val_loss: 7.9963 - val_accuracy: 0.3431
Epoch 8527/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0082 - accuracy: 1.0000 - val_loss: 7.9970 - val_accuracy: 0.3430
Epoch 8528/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0081 - accuracy: 1.0000 - val_loss: 7.9978 - val_accuracy: 0.3431
Epoch 8529/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0081 - accuracy: 1.0000 - val_loss: 7.9985 - val_accuracy: 0.3431
Epoch 8530/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0081 - accuracy: 1.0000 - val_loss: 7.9994 - val_accuracy: 0.3431
Epoch 8531/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0081 - accuracy: 1.0000 - val_loss: 8.0003 - val_accuracy: 0.3431
Epoch 8532/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0081 - accuracy: 1.0000 - val_loss: 8.0013 - val_accuracy: 0.3431
Epoch 8533/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0081 - accuracy: 1.0000 - val_loss: 8.0021 - val_accuracy: 0.3431
Epoch 8534/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0081 - accuracy: 1.0000 - val_loss: 8.0028 - val_accuracy: 0.3431
Epoch 8535/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0081 - accuracy: 1.0000 - val_loss: 8.0035 - val_accuracy: 0.3430
Epoch 8536/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0081 - accuracy: 1.0000 - val_loss: 8.0042 - val_accuracy: 0.3431
Epoch 8537/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0081 - accuracy: 1.0000 - val_loss: 8.0050 - val_accuracy: 0.3431
Epoch 8538/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0081 - accuracy: 1.0000 - val_loss: 8.0059 - val_accuracy: 0.3430
Epoch 8539/10000
1/1 [==============================] - 0s 121ms/step - loss: 0.0081 - accuracy: 1.0000 - val_loss: 8.0068 - val_accuracy: 0.3431
Epoch 8540/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0081 - accuracy: 1.0000 - val_loss: 8.0076 - val_accuracy: 0.3431
Epoch 8541/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0081 - accuracy: 1.0000 - val_loss: 8.0085 - val_accuracy: 0.3431
Epoch 8542/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0080 - accuracy: 1.0000 - val_loss: 8.0093 - val_accuracy: 0.3430
Epoch 8543/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0080 - accuracy: 1.0000 - val_loss: 8.0100 - val_accuracy: 0.3430
Epoch 8544/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0080 - accuracy: 1.0000 - val_loss: 8.0106 - val_accuracy: 0.3431
Epoch 8545/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0080 - accuracy: 1.0000 - val_loss: 8.0114 - val_accuracy: 0.3431
Epoch 8546/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0080 - accuracy: 1.0000 - val_loss: 8.0125 - val_accuracy: 0.3431
Epoch 8547/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0080 - accuracy: 1.0000 - val_loss: 8.0136 - val_accuracy: 0.3429
Epoch 8548/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0080 - accuracy: 1.0000 - val_loss: 8.0145 - val_accuracy: 0.3431
Epoch 8549/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0080 - accuracy: 1.0000 - val_loss: 8.0152 - val_accuracy: 0.3430
Epoch 8550/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0080 - accuracy: 1.0000 - val_loss: 8.0156 - val_accuracy: 0.3431
Epoch 8551/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0080 - accuracy: 1.0000 - val_loss: 8.0162 - val_accuracy: 0.3431
Epoch 8552/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0080 - accuracy: 1.0000 - val_loss: 8.0170 - val_accuracy: 0.3431
Epoch 8553/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0080 - accuracy: 1.0000 - val_loss: 8.0179 - val_accuracy: 0.3431
Epoch 8554/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0080 - accuracy: 1.0000 - val_loss: 8.0187 - val_accuracy: 0.3431
Epoch 8555/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0080 - accuracy: 1.0000 - val_loss: 8.0197 - val_accuracy: 0.3430
Epoch 8556/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0079 - accuracy: 1.0000 - val_loss: 8.0205 - val_accuracy: 0.3431
Epoch 8557/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0079 - accuracy: 1.0000 - val_loss: 8.0211 - val_accuracy: 0.3430
Epoch 8558/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0079 - accuracy: 1.0000 - val_loss: 8.0218 - val_accuracy: 0.3430
Epoch 8559/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0079 - accuracy: 1.0000 - val_loss: 8.0226 - val_accuracy: 0.3430
Epoch 8560/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0079 - accuracy: 1.0000 - val_loss: 8.0235 - val_accuracy: 0.3430
Epoch 8561/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0079 - accuracy: 1.0000 - val_loss: 8.0244 - val_accuracy: 0.3432
Epoch 8562/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0079 - accuracy: 1.0000 - val_loss: 8.0254 - val_accuracy: 0.3431
Epoch 8563/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0079 - accuracy: 1.0000 - val_loss: 8.0263 - val_accuracy: 0.3432
Epoch 8564/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0079 - accuracy: 1.0000 - val_loss: 8.0268 - val_accuracy: 0.3431
Epoch 8565/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0079 - accuracy: 1.0000 - val_loss: 8.0275 - val_accuracy: 0.3432
Epoch 8566/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0079 - accuracy: 1.0000 - val_loss: 8.0282 - val_accuracy: 0.3432
Epoch 8567/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0079 - accuracy: 1.0000 - val_loss: 8.0291 - val_accuracy: 0.3432
Epoch 8568/10000
1/1 [==============================] - 0s 116ms/step - loss: 0.0079 - accuracy: 1.0000 - val_loss: 8.0300 - val_accuracy: 0.3434
Epoch 8569/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0078 - accuracy: 1.0000 - val_loss: 8.0310 - val_accuracy: 0.3434
Epoch 8570/10000
1/1 [==============================] - 0s 116ms/step - loss: 0.0078 - accuracy: 1.0000 - val_loss: 8.0318 - val_accuracy: 0.3433
Epoch 8571/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0078 - accuracy: 1.0000 - val_loss: 8.0326 - val_accuracy: 0.3433
Epoch 8572/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0078 - accuracy: 1.0000 - val_loss: 8.0333 - val_accuracy: 0.3433
Epoch 8573/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0078 - accuracy: 1.0000 - val_loss: 8.0341 - val_accuracy: 0.3433
Epoch 8574/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0078 - accuracy: 1.0000 - val_loss: 8.0350 - val_accuracy: 0.3433
Epoch 8575/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0078 - accuracy: 1.0000 - val_loss: 8.0357 - val_accuracy: 0.3434
Epoch 8576/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0078 - accuracy: 1.0000 - val_loss: 8.0365 - val_accuracy: 0.3434
Epoch 8577/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0078 - accuracy: 1.0000 - val_loss: 8.0373 - val_accuracy: 0.3433
Epoch 8578/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0078 - accuracy: 1.0000 - val_loss: 8.0381 - val_accuracy: 0.3434
Epoch 8579/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0078 - accuracy: 1.0000 - val_loss: 8.0390 - val_accuracy: 0.3434
Epoch 8580/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0078 - accuracy: 1.0000 - val_loss: 8.0397 - val_accuracy: 0.3434
Epoch 8581/10000
1/1 [==============================] - 0s 121ms/step - loss: 0.0078 - accuracy: 1.0000 - val_loss: 8.0405 - val_accuracy: 0.3434
Epoch 8582/10000
1/1 [==============================] - 0s 119ms/step - loss: 0.0078 - accuracy: 1.0000 - val_loss: 8.0411 - val_accuracy: 0.3435
Epoch 8583/10000
1/1 [==============================] - 0s 124ms/step - loss: 0.0077 - accuracy: 1.0000 - val_loss: 8.0418 - val_accuracy: 0.3434
Epoch 8584/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0077 - accuracy: 1.0000 - val_loss: 8.0426 - val_accuracy: 0.3434
Epoch 8585/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0077 - accuracy: 1.0000 - val_loss: 8.0436 - val_accuracy: 0.3435
Epoch 8586/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0077 - accuracy: 1.0000 - val_loss: 8.0446 - val_accuracy: 0.3435
Epoch 8587/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0077 - accuracy: 1.0000 - val_loss: 8.0455 - val_accuracy: 0.3435
Epoch 8588/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0077 - accuracy: 1.0000 - val_loss: 8.0464 - val_accuracy: 0.3434
Epoch 8589/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0077 - accuracy: 1.0000 - val_loss: 8.0468 - val_accuracy: 0.3433
Epoch 8590/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0077 - accuracy: 1.0000 - val_loss: 8.0474 - val_accuracy: 0.3434
Epoch 8591/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0077 - accuracy: 1.0000 - val_loss: 8.0480 - val_accuracy: 0.3434
Epoch 8592/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0077 - accuracy: 1.0000 - val_loss: 8.0489 - val_accuracy: 0.3434
Epoch 8593/10000
1/1 [==============================] - 0s 120ms/step - loss: 0.0077 - accuracy: 1.0000 - val_loss: 8.0499 - val_accuracy: 0.3435
Epoch 8594/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0077 - accuracy: 1.0000 - val_loss: 8.0509 - val_accuracy: 0.3434
Epoch 8595/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0077 - accuracy: 1.0000 - val_loss: 8.0518 - val_accuracy: 0.3435
Epoch 8596/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0077 - accuracy: 1.0000 - val_loss: 8.0526 - val_accuracy: 0.3434
Epoch 8597/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0076 - accuracy: 1.0000 - val_loss: 8.0533 - val_accuracy: 0.3434
Epoch 8598/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0076 - accuracy: 1.0000 - val_loss: 8.0541 - val_accuracy: 0.3433
Epoch 8599/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0076 - accuracy: 1.0000 - val_loss: 8.0548 - val_accuracy: 0.3434
Epoch 8600/10000
1/1 [==============================] - 0s 117ms/step - loss: 0.0076 - accuracy: 1.0000 - val_loss: 8.0557 - val_accuracy: 0.3434
Epoch 8601/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0076 - accuracy: 1.0000 - val_loss: 8.0567 - val_accuracy: 0.3434
Epoch 8602/10000
1/1 [==============================] - 0s 117ms/step - loss: 0.0076 - accuracy: 1.0000 - val_loss: 8.0575 - val_accuracy: 0.3433
Epoch 8603/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0076 - accuracy: 1.0000 - val_loss: 8.0582 - val_accuracy: 0.3433
Epoch 8604/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0076 - accuracy: 1.0000 - val_loss: 8.0589 - val_accuracy: 0.3433
Epoch 8605/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0076 - accuracy: 1.0000 - val_loss: 8.0594 - val_accuracy: 0.3434
Epoch 8606/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0076 - accuracy: 1.0000 - val_loss: 8.0601 - val_accuracy: 0.3435
Epoch 8607/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0076 - accuracy: 1.0000 - val_loss: 8.0610 - val_accuracy: 0.3433
Epoch 8608/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0076 - accuracy: 1.0000 - val_loss: 8.0621 - val_accuracy: 0.3434
Epoch 8609/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0076 - accuracy: 1.0000 - val_loss: 8.0631 - val_accuracy: 0.3435
Epoch 8610/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0076 - accuracy: 1.0000 - val_loss: 8.0640 - val_accuracy: 0.3434
Epoch 8611/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0076 - accuracy: 1.0000 - val_loss: 8.0647 - val_accuracy: 0.3435
Epoch 8612/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0075 - accuracy: 1.0000 - val_loss: 8.0654 - val_accuracy: 0.3435
Epoch 8613/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0075 - accuracy: 1.0000 - val_loss: 8.0661 - val_accuracy: 0.3434
Epoch 8614/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0075 - accuracy: 1.0000 - val_loss: 8.0669 - val_accuracy: 0.3435
Epoch 8615/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0075 - accuracy: 1.0000 - val_loss: 8.0678 - val_accuracy: 0.3434
Epoch 8616/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0075 - accuracy: 1.0000 - val_loss: 8.0686 - val_accuracy: 0.3435
Epoch 8617/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0075 - accuracy: 1.0000 - val_loss: 8.0695 - val_accuracy: 0.3435
Epoch 8618/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0075 - accuracy: 1.0000 - val_loss: 8.0703 - val_accuracy: 0.3435
Epoch 8619/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0075 - accuracy: 1.0000 - val_loss: 8.0711 - val_accuracy: 0.3434
Epoch 8620/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0075 - accuracy: 1.0000 - val_loss: 8.0719 - val_accuracy: 0.3436
Epoch 8621/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0075 - accuracy: 1.0000 - val_loss: 8.0725 - val_accuracy: 0.3435
Epoch 8622/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0075 - accuracy: 1.0000 - val_loss: 8.0732 - val_accuracy: 0.3435
Epoch 8623/10000
1/1 [==============================] - 0s 103ms/step - loss: 0.0075 - accuracy: 1.0000 - val_loss: 8.0739 - val_accuracy: 0.3435
Epoch 8624/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0075 - accuracy: 1.0000 - val_loss: 8.0747 - val_accuracy: 0.3434
Epoch 8625/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0075 - accuracy: 1.0000 - val_loss: 8.0753 - val_accuracy: 0.3435
Epoch 8626/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0075 - accuracy: 1.0000 - val_loss: 8.0761 - val_accuracy: 0.3435
Epoch 8627/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0074 - accuracy: 1.0000 - val_loss: 8.0770 - val_accuracy: 0.3439
Epoch 8628/10000
1/1 [==============================] - 0s 117ms/step - loss: 0.0074 - accuracy: 1.0000 - val_loss: 8.0779 - val_accuracy: 0.3438
Epoch 8629/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0074 - accuracy: 1.0000 - val_loss: 8.0788 - val_accuracy: 0.3437
Epoch 8630/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0074 - accuracy: 1.0000 - val_loss: 8.0797 - val_accuracy: 0.3439
Epoch 8631/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0074 - accuracy: 1.0000 - val_loss: 8.0803 - val_accuracy: 0.3438
Epoch 8632/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0074 - accuracy: 1.0000 - val_loss: 8.0809 - val_accuracy: 0.3436
Epoch 8633/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0074 - accuracy: 1.0000 - val_loss: 8.0817 - val_accuracy: 0.3435
Epoch 8634/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0074 - accuracy: 1.0000 - val_loss: 8.0826 - val_accuracy: 0.3434
Epoch 8635/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0074 - accuracy: 1.0000 - val_loss: 8.0836 - val_accuracy: 0.3438
Epoch 8636/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0074 - accuracy: 1.0000 - val_loss: 8.0845 - val_accuracy: 0.3437
Epoch 8637/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0074 - accuracy: 1.0000 - val_loss: 8.0853 - val_accuracy: 0.3437
Epoch 8638/10000
1/1 [==============================] - 0s 117ms/step - loss: 0.0074 - accuracy: 1.0000 - val_loss: 8.0860 - val_accuracy: 0.3436
Epoch 8639/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0074 - accuracy: 1.0000 - val_loss: 8.0868 - val_accuracy: 0.3436
Epoch 8640/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0074 - accuracy: 1.0000 - val_loss: 8.0876 - val_accuracy: 0.3438
Epoch 8641/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0074 - accuracy: 1.0000 - val_loss: 8.0885 - val_accuracy: 0.3438
Epoch 8642/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0073 - accuracy: 1.0000 - val_loss: 8.0895 - val_accuracy: 0.3438
Epoch 8643/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0073 - accuracy: 1.0000 - val_loss: 8.0902 - val_accuracy: 0.3439
Epoch 8644/10000
1/1 [==============================] - 0s 104ms/step - loss: 0.0073 - accuracy: 1.0000 - val_loss: 8.0908 - val_accuracy: 0.3436
Epoch 8645/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0073 - accuracy: 1.0000 - val_loss: 8.0913 - val_accuracy: 0.3437
Epoch 8646/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0073 - accuracy: 1.0000 - val_loss: 8.0920 - val_accuracy: 0.3437
Epoch 8647/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0073 - accuracy: 1.0000 - val_loss: 8.0927 - val_accuracy: 0.3435
Epoch 8648/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0073 - accuracy: 1.0000 - val_loss: 8.0936 - val_accuracy: 0.3437
Epoch 8649/10000
1/1 [==============================] - 0s 103ms/step - loss: 0.0073 - accuracy: 1.0000 - val_loss: 8.0946 - val_accuracy: 0.3436
Epoch 8650/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0073 - accuracy: 1.0000 - val_loss: 8.0956 - val_accuracy: 0.3438
Epoch 8651/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0073 - accuracy: 1.0000 - val_loss: 8.0962 - val_accuracy: 0.3438
Epoch 8652/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0073 - accuracy: 1.0000 - val_loss: 8.0969 - val_accuracy: 0.3439
Epoch 8653/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0073 - accuracy: 1.0000 - val_loss: 8.0975 - val_accuracy: 0.3439
Epoch 8654/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0073 - accuracy: 1.0000 - val_loss: 8.0982 - val_accuracy: 0.3439
Epoch 8655/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0073 - accuracy: 1.0000 - val_loss: 8.0990 - val_accuracy: 0.3439
Epoch 8656/10000
1/1 [==============================] - 0s 104ms/step - loss: 0.0073 - accuracy: 1.0000 - val_loss: 8.1000 - val_accuracy: 0.3439
Epoch 8657/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0072 - accuracy: 1.0000 - val_loss: 8.1010 - val_accuracy: 0.3438
Epoch 8658/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0072 - accuracy: 1.0000 - val_loss: 8.1017 - val_accuracy: 0.3438
Epoch 8659/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0072 - accuracy: 1.0000 - val_loss: 8.1024 - val_accuracy: 0.3436
Epoch 8660/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0072 - accuracy: 1.0000 - val_loss: 8.1030 - val_accuracy: 0.3437
Epoch 8661/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0072 - accuracy: 1.0000 - val_loss: 8.1038 - val_accuracy: 0.3437
Epoch 8662/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0072 - accuracy: 1.0000 - val_loss: 8.1047 - val_accuracy: 0.3438
Epoch 8663/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0072 - accuracy: 1.0000 - val_loss: 8.1056 - val_accuracy: 0.3438
Epoch 8664/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0072 - accuracy: 1.0000 - val_loss: 8.1066 - val_accuracy: 0.3438
Epoch 8665/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0072 - accuracy: 1.0000 - val_loss: 8.1073 - val_accuracy: 0.3439
Epoch 8666/10000
1/1 [==============================] - 0s 104ms/step - loss: 0.0072 - accuracy: 1.0000 - val_loss: 8.1080 - val_accuracy: 0.3439
Epoch 8667/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0072 - accuracy: 1.0000 - val_loss: 8.1087 - val_accuracy: 0.3439
Epoch 8668/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0072 - accuracy: 1.0000 - val_loss: 8.1094 - val_accuracy: 0.3440
Epoch 8669/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0072 - accuracy: 1.0000 - val_loss: 8.1102 - val_accuracy: 0.3438
Epoch 8670/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0072 - accuracy: 1.0000 - val_loss: 8.1109 - val_accuracy: 0.3438
Epoch 8671/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0072 - accuracy: 1.0000 - val_loss: 8.1118 - val_accuracy: 0.3437
Epoch 8672/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0071 - accuracy: 1.0000 - val_loss: 8.1127 - val_accuracy: 0.3437
Epoch 8673/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0071 - accuracy: 1.0000 - val_loss: 8.1136 - val_accuracy: 0.3438
Epoch 8674/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0071 - accuracy: 1.0000 - val_loss: 8.1143 - val_accuracy: 0.3437
Epoch 8675/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0071 - accuracy: 1.0000 - val_loss: 8.1150 - val_accuracy: 0.3438
Epoch 8676/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0071 - accuracy: 1.0000 - val_loss: 8.1158 - val_accuracy: 0.3438
Epoch 8677/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0071 - accuracy: 1.0000 - val_loss: 8.1165 - val_accuracy: 0.3439
Epoch 8678/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0071 - accuracy: 1.0000 - val_loss: 8.1172 - val_accuracy: 0.3438
Epoch 8679/10000
1/1 [==============================] - 0s 116ms/step - loss: 0.0071 - accuracy: 1.0000 - val_loss: 8.1179 - val_accuracy: 0.3438
Epoch 8680/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0071 - accuracy: 1.0000 - val_loss: 8.1188 - val_accuracy: 0.3438
Epoch 8681/10000
1/1 [==============================] - 0s 119ms/step - loss: 0.0071 - accuracy: 1.0000 - val_loss: 8.1196 - val_accuracy: 0.3438
Epoch 8682/10000
1/1 [==============================] - 0s 124ms/step - loss: 0.0071 - accuracy: 1.0000 - val_loss: 8.1204 - val_accuracy: 0.3438
Epoch 8683/10000
1/1 [==============================] - 0s 131ms/step - loss: 0.0071 - accuracy: 1.0000 - val_loss: 8.1211 - val_accuracy: 0.3439
Epoch 8684/10000
1/1 [==============================] - 0s 132ms/step - loss: 0.0071 - accuracy: 1.0000 - val_loss: 8.1219 - val_accuracy: 0.3439
Epoch 8685/10000
1/1 [==============================] - 0s 118ms/step - loss: 0.0071 - accuracy: 1.0000 - val_loss: 8.1227 - val_accuracy: 0.3439
Epoch 8686/10000
1/1 [==============================] - 0s 121ms/step - loss: 0.0071 - accuracy: 1.0000 - val_loss: 8.1234 - val_accuracy: 0.3439
Epoch 8687/10000
1/1 [==============================] - 0s 124ms/step - loss: 0.0071 - accuracy: 1.0000 - val_loss: 8.1243 - val_accuracy: 0.3438
Epoch 8688/10000
1/1 [==============================] - 0s 128ms/step - loss: 0.0070 - accuracy: 1.0000 - val_loss: 8.1252 - val_accuracy: 0.3438
Epoch 8689/10000
1/1 [==============================] - 0s 117ms/step - loss: 0.0070 - accuracy: 1.0000 - val_loss: 8.1260 - val_accuracy: 0.3438
Epoch 8690/10000
1/1 [==============================] - 0s 123ms/step - loss: 0.0070 - accuracy: 1.0000 - val_loss: 8.1269 - val_accuracy: 0.3439
Epoch 8691/10000
1/1 [==============================] - 0s 120ms/step - loss: 0.0070 - accuracy: 1.0000 - val_loss: 8.1275 - val_accuracy: 0.3439
Epoch 8692/10000
1/1 [==============================] - 0s 123ms/step - loss: 0.0070 - accuracy: 1.0000 - val_loss: 8.1281 - val_accuracy: 0.3438
Epoch 8693/10000
1/1 [==============================] - 0s 125ms/step - loss: 0.0070 - accuracy: 1.0000 - val_loss: 8.1290 - val_accuracy: 0.3436
Epoch 8694/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0070 - accuracy: 1.0000 - val_loss: 8.1300 - val_accuracy: 0.3438
Epoch 8695/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0070 - accuracy: 1.0000 - val_loss: 8.1309 - val_accuracy: 0.3436
Epoch 8696/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0070 - accuracy: 1.0000 - val_loss: 8.1316 - val_accuracy: 0.3437
Epoch 8697/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0070 - accuracy: 1.0000 - val_loss: 8.1322 - val_accuracy: 0.3438
Epoch 8698/10000
1/1 [==============================] - 0s 116ms/step - loss: 0.0070 - accuracy: 1.0000 - val_loss: 8.1327 - val_accuracy: 0.3436
Epoch 8699/10000
1/1 [==============================] - 0s 121ms/step - loss: 0.0070 - accuracy: 1.0000 - val_loss: 8.1334 - val_accuracy: 0.3438
Epoch 8700/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0070 - accuracy: 1.0000 - val_loss: 8.1341 - val_accuracy: 0.3436
Epoch 8701/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0070 - accuracy: 1.0000 - val_loss: 8.1350 - val_accuracy: 0.3436
Epoch 8702/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0070 - accuracy: 1.0000 - val_loss: 8.1359 - val_accuracy: 0.3436
Epoch 8703/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0070 - accuracy: 1.0000 - val_loss: 8.1368 - val_accuracy: 0.3436
Epoch 8704/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0069 - accuracy: 1.0000 - val_loss: 8.1375 - val_accuracy: 0.3436
Epoch 8705/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0069 - accuracy: 1.0000 - val_loss: 8.1383 - val_accuracy: 0.3436
Epoch 8706/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0069 - accuracy: 1.0000 - val_loss: 8.1390 - val_accuracy: 0.3437
Epoch 8707/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0069 - accuracy: 1.0000 - val_loss: 8.1398 - val_accuracy: 0.3437
Epoch 8708/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0069 - accuracy: 1.0000 - val_loss: 8.1406 - val_accuracy: 0.3437
Epoch 8709/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0069 - accuracy: 1.0000 - val_loss: 8.1415 - val_accuracy: 0.3437
Epoch 8710/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0069 - accuracy: 1.0000 - val_loss: 8.1421 - val_accuracy: 0.3437
Epoch 8711/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0069 - accuracy: 1.0000 - val_loss: 8.1429 - val_accuracy: 0.3436
Epoch 8712/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0069 - accuracy: 1.0000 - val_loss: 8.1439 - val_accuracy: 0.3437
Epoch 8713/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0069 - accuracy: 1.0000 - val_loss: 8.1450 - val_accuracy: 0.3436
Epoch 8714/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0069 - accuracy: 1.0000 - val_loss: 8.1459 - val_accuracy: 0.3437
Epoch 8715/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0069 - accuracy: 1.0000 - val_loss: 8.1466 - val_accuracy: 0.3436
Epoch 8716/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0069 - accuracy: 1.0000 - val_loss: 8.1470 - val_accuracy: 0.3436
Epoch 8717/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0069 - accuracy: 1.0000 - val_loss: 8.1476 - val_accuracy: 0.3434
Epoch 8718/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0069 - accuracy: 1.0000 - val_loss: 8.1483 - val_accuracy: 0.3436
Epoch 8719/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0069 - accuracy: 1.0000 - val_loss: 8.1491 - val_accuracy: 0.3434
Epoch 8720/10000
1/1 [==============================] - 0s 121ms/step - loss: 0.0068 - accuracy: 1.0000 - val_loss: 8.1500 - val_accuracy: 0.3435
Epoch 8721/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0068 - accuracy: 1.0000 - val_loss: 8.1509 - val_accuracy: 0.3434
Epoch 8722/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0068 - accuracy: 1.0000 - val_loss: 8.1518 - val_accuracy: 0.3435
Epoch 8723/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0068 - accuracy: 1.0000 - val_loss: 8.1525 - val_accuracy: 0.3437
Epoch 8724/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0068 - accuracy: 1.0000 - val_loss: 8.1531 - val_accuracy: 0.3437
Epoch 8725/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0068 - accuracy: 1.0000 - val_loss: 8.1538 - val_accuracy: 0.3437
Epoch 8726/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0068 - accuracy: 1.0000 - val_loss: 8.1546 - val_accuracy: 0.3436
Epoch 8727/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0068 - accuracy: 1.0000 - val_loss: 8.1556 - val_accuracy: 0.3435
Epoch 8728/10000
1/1 [==============================] - 0s 116ms/step - loss: 0.0068 - accuracy: 1.0000 - val_loss: 8.1565 - val_accuracy: 0.3435
Epoch 8729/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0068 - accuracy: 1.0000 - val_loss: 8.1572 - val_accuracy: 0.3437
Epoch 8730/10000
1/1 [==============================] - 0s 116ms/step - loss: 0.0068 - accuracy: 1.0000 - val_loss: 8.1579 - val_accuracy: 0.3439
Epoch 8731/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0068 - accuracy: 1.0000 - val_loss: 8.1584 - val_accuracy: 0.3438
Epoch 8732/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0068 - accuracy: 1.0000 - val_loss: 8.1592 - val_accuracy: 0.3436
Epoch 8733/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0068 - accuracy: 1.0000 - val_loss: 8.1601 - val_accuracy: 0.3437
Epoch 8734/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0068 - accuracy: 1.0000 - val_loss: 8.1610 - val_accuracy: 0.3438
Epoch 8735/10000
1/1 [==============================] - 0s 117ms/step - loss: 0.0068 - accuracy: 1.0000 - val_loss: 8.1619 - val_accuracy: 0.3435
Epoch 8736/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0067 - accuracy: 1.0000 - val_loss: 8.1628 - val_accuracy: 0.3437
Epoch 8737/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0067 - accuracy: 1.0000 - val_loss: 8.1635 - val_accuracy: 0.3435
Epoch 8738/10000
1/1 [==============================] - 0s 122ms/step - loss: 0.0067 - accuracy: 1.0000 - val_loss: 8.1642 - val_accuracy: 0.3436
Epoch 8739/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0067 - accuracy: 1.0000 - val_loss: 8.1647 - val_accuracy: 0.3435
Epoch 8740/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0067 - accuracy: 1.0000 - val_loss: 8.1653 - val_accuracy: 0.3436
Epoch 8741/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0067 - accuracy: 1.0000 - val_loss: 8.1660 - val_accuracy: 0.3435
Epoch 8742/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0067 - accuracy: 1.0000 - val_loss: 8.1668 - val_accuracy: 0.3433
Epoch 8743/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0067 - accuracy: 1.0000 - val_loss: 8.1677 - val_accuracy: 0.3435
Epoch 8744/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0067 - accuracy: 1.0000 - val_loss: 8.1686 - val_accuracy: 0.3434
Epoch 8745/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0067 - accuracy: 1.0000 - val_loss: 8.1693 - val_accuracy: 0.3437
Epoch 8746/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0067 - accuracy: 1.0000 - val_loss: 8.1702 - val_accuracy: 0.3434
Epoch 8747/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0067 - accuracy: 1.0000 - val_loss: 8.1709 - val_accuracy: 0.3435
Epoch 8748/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0067 - accuracy: 1.0000 - val_loss: 8.1715 - val_accuracy: 0.3435
Epoch 8749/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0067 - accuracy: 1.0000 - val_loss: 8.1723 - val_accuracy: 0.3434
Epoch 8750/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0067 - accuracy: 1.0000 - val_loss: 8.1733 - val_accuracy: 0.3435
Epoch 8751/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0067 - accuracy: 1.0000 - val_loss: 8.1743 - val_accuracy: 0.3436
Epoch 8752/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0067 - accuracy: 1.0000 - val_loss: 8.1750 - val_accuracy: 0.3435
Epoch 8753/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0066 - accuracy: 1.0000 - val_loss: 8.1758 - val_accuracy: 0.3434
Epoch 8754/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0066 - accuracy: 1.0000 - val_loss: 8.1764 - val_accuracy: 0.3434
Epoch 8755/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0066 - accuracy: 1.0000 - val_loss: 8.1770 - val_accuracy: 0.3435
Epoch 8756/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0066 - accuracy: 1.0000 - val_loss: 8.1779 - val_accuracy: 0.3435
Epoch 8757/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0066 - accuracy: 1.0000 - val_loss: 8.1788 - val_accuracy: 0.3435
Epoch 8758/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0066 - accuracy: 1.0000 - val_loss: 8.1797 - val_accuracy: 0.3437
Epoch 8759/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0066 - accuracy: 1.0000 - val_loss: 8.1803 - val_accuracy: 0.3437
Epoch 8760/10000
1/1 [==============================] - 0s 117ms/step - loss: 0.0066 - accuracy: 1.0000 - val_loss: 8.1810 - val_accuracy: 0.3437
Epoch 8761/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0066 - accuracy: 1.0000 - val_loss: 8.1817 - val_accuracy: 0.3436
Epoch 8762/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0066 - accuracy: 1.0000 - val_loss: 8.1823 - val_accuracy: 0.3435
Epoch 8763/10000
1/1 [==============================] - 0s 116ms/step - loss: 0.0066 - accuracy: 1.0000 - val_loss: 8.1831 - val_accuracy: 0.3436
Epoch 8764/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0066 - accuracy: 1.0000 - val_loss: 8.1840 - val_accuracy: 0.3436
Epoch 8765/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0066 - accuracy: 1.0000 - val_loss: 8.1850 - val_accuracy: 0.3437
Epoch 8766/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0066 - accuracy: 1.0000 - val_loss: 8.1860 - val_accuracy: 0.3436
Epoch 8767/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0066 - accuracy: 1.0000 - val_loss: 8.1866 - val_accuracy: 0.3437
Epoch 8768/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0066 - accuracy: 1.0000 - val_loss: 8.1873 - val_accuracy: 0.3437
Epoch 8769/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0066 - accuracy: 1.0000 - val_loss: 8.1881 - val_accuracy: 0.3438
Epoch 8770/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0065 - accuracy: 1.0000 - val_loss: 8.1888 - val_accuracy: 0.3437
Epoch 8771/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0065 - accuracy: 1.0000 - val_loss: 8.1894 - val_accuracy: 0.3436
Epoch 8772/10000
1/1 [==============================] - 0s 117ms/step - loss: 0.0065 - accuracy: 1.0000 - val_loss: 8.1900 - val_accuracy: 0.3437
Epoch 8773/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0065 - accuracy: 1.0000 - val_loss: 8.1907 - val_accuracy: 0.3437
Epoch 8774/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0065 - accuracy: 1.0000 - val_loss: 8.1916 - val_accuracy: 0.3436
Epoch 8775/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0065 - accuracy: 1.0000 - val_loss: 8.1925 - val_accuracy: 0.3435
Epoch 8776/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0065 - accuracy: 1.0000 - val_loss: 8.1934 - val_accuracy: 0.3436
Epoch 8777/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0065 - accuracy: 1.0000 - val_loss: 8.1943 - val_accuracy: 0.3436
Epoch 8778/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0065 - accuracy: 1.0000 - val_loss: 8.1951 - val_accuracy: 0.3436
Epoch 8779/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0065 - accuracy: 1.0000 - val_loss: 8.1959 - val_accuracy: 0.3435
Epoch 8780/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0065 - accuracy: 1.0000 - val_loss: 8.1967 - val_accuracy: 0.3435
Epoch 8781/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0065 - accuracy: 1.0000 - val_loss: 8.1974 - val_accuracy: 0.3436
Epoch 8782/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0065 - accuracy: 1.0000 - val_loss: 8.1981 - val_accuracy: 0.3435
Epoch 8783/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0065 - accuracy: 1.0000 - val_loss: 8.1988 - val_accuracy: 0.3436
Epoch 8784/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0065 - accuracy: 1.0000 - val_loss: 8.1996 - val_accuracy: 0.3436
Epoch 8785/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0065 - accuracy: 1.0000 - val_loss: 8.2004 - val_accuracy: 0.3436
Epoch 8786/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0065 - accuracy: 1.0000 - val_loss: 8.2012 - val_accuracy: 0.3436
Epoch 8787/10000
1/1 [==============================] - 0s 121ms/step - loss: 0.0065 - accuracy: 1.0000 - val_loss: 8.2017 - val_accuracy: 0.3436
Epoch 8788/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0064 - accuracy: 1.0000 - val_loss: 8.2022 - val_accuracy: 0.3435
Epoch 8789/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0064 - accuracy: 1.0000 - val_loss: 8.2030 - val_accuracy: 0.3435
Epoch 8790/10000
1/1 [==============================] - 0s 121ms/step - loss: 0.0064 - accuracy: 1.0000 - val_loss: 8.2038 - val_accuracy: 0.3435
Epoch 8791/10000
1/1 [==============================] - 0s 116ms/step - loss: 0.0064 - accuracy: 1.0000 - val_loss: 8.2047 - val_accuracy: 0.3436
Epoch 8792/10000
1/1 [==============================] - 0s 121ms/step - loss: 0.0064 - accuracy: 1.0000 - val_loss: 8.2056 - val_accuracy: 0.3436
Epoch 8793/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0064 - accuracy: 1.0000 - val_loss: 8.2064 - val_accuracy: 0.3436
Epoch 8794/10000
1/1 [==============================] - 0s 117ms/step - loss: 0.0064 - accuracy: 1.0000 - val_loss: 8.2071 - val_accuracy: 0.3434
Epoch 8795/10000
1/1 [==============================] - 0s 116ms/step - loss: 0.0064 - accuracy: 1.0000 - val_loss: 8.2078 - val_accuracy: 0.3436
Epoch 8796/10000
1/1 [==============================] - 0s 116ms/step - loss: 0.0064 - accuracy: 1.0000 - val_loss: 8.2086 - val_accuracy: 0.3435
Epoch 8797/10000
1/1 [==============================] - 0s 120ms/step - loss: 0.0064 - accuracy: 1.0000 - val_loss: 8.2094 - val_accuracy: 0.3436
Epoch 8798/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0064 - accuracy: 1.0000 - val_loss: 8.2103 - val_accuracy: 0.3436
Epoch 8799/10000
1/1 [==============================] - 0s 118ms/step - loss: 0.0064 - accuracy: 1.0000 - val_loss: 8.2111 - val_accuracy: 0.3436
Epoch 8800/10000
1/1 [==============================] - 0s 116ms/step - loss: 0.0064 - accuracy: 1.0000 - val_loss: 8.2119 - val_accuracy: 0.3435
Epoch 8801/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0064 - accuracy: 1.0000 - val_loss: 8.2125 - val_accuracy: 0.3435
Epoch 8802/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0064 - accuracy: 1.0000 - val_loss: 8.2132 - val_accuracy: 0.3435
Epoch 8803/10000
1/1 [==============================] - 0s 116ms/step - loss: 0.0064 - accuracy: 1.0000 - val_loss: 8.2138 - val_accuracy: 0.3436
Epoch 8804/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0064 - accuracy: 1.0000 - val_loss: 8.2144 - val_accuracy: 0.3436
Epoch 8805/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0063 - accuracy: 1.0000 - val_loss: 8.2153 - val_accuracy: 0.3436
Epoch 8806/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0063 - accuracy: 1.0000 - val_loss: 8.2161 - val_accuracy: 0.3437
Epoch 8807/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0063 - accuracy: 1.0000 - val_loss: 8.2168 - val_accuracy: 0.3435
Epoch 8808/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0063 - accuracy: 1.0000 - val_loss: 8.2176 - val_accuracy: 0.3435
Epoch 8809/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0063 - accuracy: 1.0000 - val_loss: 8.2184 - val_accuracy: 0.3436
Epoch 8810/10000
1/1 [==============================] - 0s 120ms/step - loss: 0.0063 - accuracy: 1.0000 - val_loss: 8.2191 - val_accuracy: 0.3435
Epoch 8811/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0063 - accuracy: 1.0000 - val_loss: 8.2199 - val_accuracy: 0.3436
Epoch 8812/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0063 - accuracy: 1.0000 - val_loss: 8.2209 - val_accuracy: 0.3435
Epoch 8813/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0063 - accuracy: 1.0000 - val_loss: 8.2217 - val_accuracy: 0.3435
Epoch 8814/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0063 - accuracy: 1.0000 - val_loss: 8.2225 - val_accuracy: 0.3435
Epoch 8815/10000
1/1 [==============================] - 0s 117ms/step - loss: 0.0063 - accuracy: 1.0000 - val_loss: 8.2232 - val_accuracy: 0.3436
Epoch 8816/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0063 - accuracy: 1.0000 - val_loss: 8.2238 - val_accuracy: 0.3436
Epoch 8817/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0063 - accuracy: 1.0000 - val_loss: 8.2245 - val_accuracy: 0.3437
Epoch 8818/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0063 - accuracy: 1.0000 - val_loss: 8.2254 - val_accuracy: 0.3436
Epoch 8819/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0063 - accuracy: 1.0000 - val_loss: 8.2262 - val_accuracy: 0.3435
Epoch 8820/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0063 - accuracy: 1.0000 - val_loss: 8.2270 - val_accuracy: 0.3434
Epoch 8821/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0063 - accuracy: 1.0000 - val_loss: 8.2279 - val_accuracy: 0.3436
Epoch 8822/10000
1/1 [==============================] - 0s 119ms/step - loss: 0.0063 - accuracy: 1.0000 - val_loss: 8.2285 - val_accuracy: 0.3434
Epoch 8823/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0062 - accuracy: 1.0000 - val_loss: 8.2292 - val_accuracy: 0.3434
Epoch 8824/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0062 - accuracy: 1.0000 - val_loss: 8.2298 - val_accuracy: 0.3434
Epoch 8825/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0062 - accuracy: 1.0000 - val_loss: 8.2307 - val_accuracy: 0.3435
Epoch 8826/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0062 - accuracy: 1.0000 - val_loss: 8.2313 - val_accuracy: 0.3434
Epoch 8827/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0062 - accuracy: 1.0000 - val_loss: 8.2321 - val_accuracy: 0.3434
Epoch 8828/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0062 - accuracy: 1.0000 - val_loss: 8.2328 - val_accuracy: 0.3434
Epoch 8829/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0062 - accuracy: 1.0000 - val_loss: 8.2334 - val_accuracy: 0.3436
Epoch 8830/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0062 - accuracy: 1.0000 - val_loss: 8.2342 - val_accuracy: 0.3435
Epoch 8831/10000
1/1 [==============================] - 0s 116ms/step - loss: 0.0062 - accuracy: 1.0000 - val_loss: 8.2351 - val_accuracy: 0.3435
Epoch 8832/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0062 - accuracy: 1.0000 - val_loss: 8.2358 - val_accuracy: 0.3433
Epoch 8833/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0062 - accuracy: 1.0000 - val_loss: 8.2366 - val_accuracy: 0.3434
Epoch 8834/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0062 - accuracy: 1.0000 - val_loss: 8.2375 - val_accuracy: 0.3434
Epoch 8835/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0062 - accuracy: 1.0000 - val_loss: 8.2383 - val_accuracy: 0.3434
Epoch 8836/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0062 - accuracy: 1.0000 - val_loss: 8.2391 - val_accuracy: 0.3434
Epoch 8837/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0062 - accuracy: 1.0000 - val_loss: 8.2399 - val_accuracy: 0.3434
Epoch 8838/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0062 - accuracy: 1.0000 - val_loss: 8.2407 - val_accuracy: 0.3435
Epoch 8839/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0062 - accuracy: 1.0000 - val_loss: 8.2413 - val_accuracy: 0.3434
Epoch 8840/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0062 - accuracy: 1.0000 - val_loss: 8.2419 - val_accuracy: 0.3434
Epoch 8841/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0062 - accuracy: 1.0000 - val_loss: 8.2427 - val_accuracy: 0.3435
Epoch 8842/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0061 - accuracy: 1.0000 - val_loss: 8.2435 - val_accuracy: 0.3434
Epoch 8843/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0061 - accuracy: 1.0000 - val_loss: 8.2440 - val_accuracy: 0.3435
Epoch 8844/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0061 - accuracy: 1.0000 - val_loss: 8.2447 - val_accuracy: 0.3434
Epoch 8845/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0061 - accuracy: 1.0000 - val_loss: 8.2454 - val_accuracy: 0.3434
Epoch 8846/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0061 - accuracy: 1.0000 - val_loss: 8.2464 - val_accuracy: 0.3434
Epoch 8847/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0061 - accuracy: 1.0000 - val_loss: 8.2473 - val_accuracy: 0.3434
Epoch 8848/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0061 - accuracy: 1.0000 - val_loss: 8.2482 - val_accuracy: 0.3435
Epoch 8849/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0061 - accuracy: 1.0000 - val_loss: 8.2490 - val_accuracy: 0.3435
Epoch 8850/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0061 - accuracy: 1.0000 - val_loss: 8.2496 - val_accuracy: 0.3435
Epoch 8851/10000
1/1 [==============================] - 0s 104ms/step - loss: 0.0061 - accuracy: 1.0000 - val_loss: 8.2500 - val_accuracy: 0.3435
Epoch 8852/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0061 - accuracy: 1.0000 - val_loss: 8.2505 - val_accuracy: 0.3435
Epoch 8853/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0061 - accuracy: 1.0000 - val_loss: 8.2513 - val_accuracy: 0.3436
Epoch 8854/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0061 - accuracy: 1.0000 - val_loss: 8.2521 - val_accuracy: 0.3435
Epoch 8855/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0061 - accuracy: 1.0000 - val_loss: 8.2531 - val_accuracy: 0.3435
Epoch 8856/10000
1/1 [==============================] - 0s 104ms/step - loss: 0.0061 - accuracy: 1.0000 - val_loss: 8.2541 - val_accuracy: 0.3434
Epoch 8857/10000
1/1 [==============================] - 0s 119ms/step - loss: 0.0061 - accuracy: 1.0000 - val_loss: 8.2549 - val_accuracy: 0.3435
Epoch 8858/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0061 - accuracy: 1.0000 - val_loss: 8.2555 - val_accuracy: 0.3435
Epoch 8859/10000
1/1 [==============================] - 0s 116ms/step - loss: 0.0061 - accuracy: 1.0000 - val_loss: 8.2562 - val_accuracy: 0.3436
Epoch 8860/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0060 - accuracy: 1.0000 - val_loss: 8.2568 - val_accuracy: 0.3435
Epoch 8861/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0060 - accuracy: 1.0000 - val_loss: 8.2573 - val_accuracy: 0.3436
Epoch 8862/10000
1/1 [==============================] - 0s 104ms/step - loss: 0.0060 - accuracy: 1.0000 - val_loss: 8.2580 - val_accuracy: 0.3437
Epoch 8863/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0060 - accuracy: 1.0000 - val_loss: 8.2588 - val_accuracy: 0.3434
Epoch 8864/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0060 - accuracy: 1.0000 - val_loss: 8.2598 - val_accuracy: 0.3435
Epoch 8865/10000
1/1 [==============================] - 0s 116ms/step - loss: 0.0060 - accuracy: 1.0000 - val_loss: 8.2605 - val_accuracy: 0.3434
Epoch 8866/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0060 - accuracy: 1.0000 - val_loss: 8.2612 - val_accuracy: 0.3434
Epoch 8867/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0060 - accuracy: 1.0000 - val_loss: 8.2618 - val_accuracy: 0.3435
Epoch 8868/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0060 - accuracy: 1.0000 - val_loss: 8.2625 - val_accuracy: 0.3436
Epoch 8869/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0060 - accuracy: 1.0000 - val_loss: 8.2633 - val_accuracy: 0.3436
Epoch 8870/10000
1/1 [==============================] - 0s 119ms/step - loss: 0.0060 - accuracy: 1.0000 - val_loss: 8.2642 - val_accuracy: 0.3436
Epoch 8871/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0060 - accuracy: 1.0000 - val_loss: 8.2651 - val_accuracy: 0.3435
Epoch 8872/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0060 - accuracy: 1.0000 - val_loss: 8.2659 - val_accuracy: 0.3437
Epoch 8873/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0060 - accuracy: 1.0000 - val_loss: 8.2668 - val_accuracy: 0.3436
Epoch 8874/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0060 - accuracy: 1.0000 - val_loss: 8.2673 - val_accuracy: 0.3437
Epoch 8875/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0060 - accuracy: 1.0000 - val_loss: 8.2679 - val_accuracy: 0.3438
Epoch 8876/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0060 - accuracy: 1.0000 - val_loss: 8.2686 - val_accuracy: 0.3438
Epoch 8877/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0060 - accuracy: 1.0000 - val_loss: 8.2694 - val_accuracy: 0.3438
Epoch 8878/10000
1/1 [==============================] - 0s 103ms/step - loss: 0.0060 - accuracy: 1.0000 - val_loss: 8.2702 - val_accuracy: 0.3439
Epoch 8879/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0059 - accuracy: 1.0000 - val_loss: 8.2711 - val_accuracy: 0.3434
Epoch 8880/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0059 - accuracy: 1.0000 - val_loss: 8.2720 - val_accuracy: 0.3436
Epoch 8881/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0059 - accuracy: 1.0000 - val_loss: 8.2727 - val_accuracy: 0.3437
Epoch 8882/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0059 - accuracy: 1.0000 - val_loss: 8.2734 - val_accuracy: 0.3435
Epoch 8883/10000
1/1 [==============================] - 0s 104ms/step - loss: 0.0059 - accuracy: 1.0000 - val_loss: 8.2741 - val_accuracy: 0.3437
Epoch 8884/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0059 - accuracy: 1.0000 - val_loss: 8.2746 - val_accuracy: 0.3436
Epoch 8885/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0059 - accuracy: 1.0000 - val_loss: 8.2753 - val_accuracy: 0.3436
Epoch 8886/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0059 - accuracy: 1.0000 - val_loss: 8.2762 - val_accuracy: 0.3438
Epoch 8887/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0059 - accuracy: 1.0000 - val_loss: 8.2773 - val_accuracy: 0.3437
Epoch 8888/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0059 - accuracy: 1.0000 - val_loss: 8.2781 - val_accuracy: 0.3436
Epoch 8889/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0059 - accuracy: 1.0000 - val_loss: 8.2786 - val_accuracy: 0.3435
Epoch 8890/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0059 - accuracy: 1.0000 - val_loss: 8.2791 - val_accuracy: 0.3437
Epoch 8891/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0059 - accuracy: 1.0000 - val_loss: 8.2796 - val_accuracy: 0.3438
Epoch 8892/10000
1/1 [==============================] - 0s 119ms/step - loss: 0.0059 - accuracy: 1.0000 - val_loss: 8.2803 - val_accuracy: 0.3437
Epoch 8893/10000
1/1 [==============================] - 0s 125ms/step - loss: 0.0059 - accuracy: 1.0000 - val_loss: 8.2813 - val_accuracy: 0.3438
Epoch 8894/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0059 - accuracy: 1.0000 - val_loss: 8.2823 - val_accuracy: 0.3436
Epoch 8895/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0059 - accuracy: 1.0000 - val_loss: 8.2834 - val_accuracy: 0.3437
Epoch 8896/10000
1/1 [==============================] - 0s 116ms/step - loss: 0.0059 - accuracy: 1.0000 - val_loss: 8.2844 - val_accuracy: 0.3435
Epoch 8897/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0059 - accuracy: 1.0000 - val_loss: 8.2850 - val_accuracy: 0.3435
Epoch 8898/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0058 - accuracy: 1.0000 - val_loss: 8.2852 - val_accuracy: 0.3436
Epoch 8899/10000
1/1 [==============================] - 0s 116ms/step - loss: 0.0058 - accuracy: 1.0000 - val_loss: 8.2855 - val_accuracy: 0.3437
Epoch 8900/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0058 - accuracy: 1.0000 - val_loss: 8.2861 - val_accuracy: 0.3437
Epoch 8901/10000
1/1 [==============================] - 0s 116ms/step - loss: 0.0058 - accuracy: 1.0000 - val_loss: 8.2867 - val_accuracy: 0.3436
Epoch 8902/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0058 - accuracy: 1.0000 - val_loss: 8.2877 - val_accuracy: 0.3436
Epoch 8903/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0058 - accuracy: 1.0000 - val_loss: 8.2888 - val_accuracy: 0.3435
Epoch 8904/10000
1/1 [==============================] - 0s 117ms/step - loss: 0.0058 - accuracy: 1.0000 - val_loss: 8.2899 - val_accuracy: 0.3434
Epoch 8905/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0058 - accuracy: 1.0000 - val_loss: 8.2909 - val_accuracy: 0.3434
Epoch 8906/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0058 - accuracy: 1.0000 - val_loss: 8.2916 - val_accuracy: 0.3435
Epoch 8907/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0058 - accuracy: 1.0000 - val_loss: 8.2922 - val_accuracy: 0.3435
Epoch 8908/10000
1/1 [==============================] - 0s 122ms/step - loss: 0.0058 - accuracy: 1.0000 - val_loss: 8.2928 - val_accuracy: 0.3436
Epoch 8909/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0058 - accuracy: 1.0000 - val_loss: 8.2935 - val_accuracy: 0.3436
Epoch 8910/10000
1/1 [==============================] - 0s 118ms/step - loss: 0.0058 - accuracy: 1.0000 - val_loss: 8.2942 - val_accuracy: 0.3437
Epoch 8911/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0058 - accuracy: 1.0000 - val_loss: 8.2951 - val_accuracy: 0.3435
Epoch 8912/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0058 - accuracy: 1.0000 - val_loss: 8.2960 - val_accuracy: 0.3434
Epoch 8913/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0058 - accuracy: 1.0000 - val_loss: 8.2968 - val_accuracy: 0.3435
Epoch 8914/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0058 - accuracy: 1.0000 - val_loss: 8.2974 - val_accuracy: 0.3434
Epoch 8915/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0058 - accuracy: 1.0000 - val_loss: 8.2980 - val_accuracy: 0.3435
Epoch 8916/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0058 - accuracy: 1.0000 - val_loss: 8.2985 - val_accuracy: 0.3434
Epoch 8917/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0058 - accuracy: 1.0000 - val_loss: 8.2991 - val_accuracy: 0.3434
Epoch 8918/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0057 - accuracy: 1.0000 - val_loss: 8.2998 - val_accuracy: 0.3433
Epoch 8919/10000
1/1 [==============================] - 0s 116ms/step - loss: 0.0057 - accuracy: 1.0000 - val_loss: 8.3005 - val_accuracy: 0.3433
Epoch 8920/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0057 - accuracy: 1.0000 - val_loss: 8.3014 - val_accuracy: 0.3434
Epoch 8921/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0057 - accuracy: 1.0000 - val_loss: 8.3023 - val_accuracy: 0.3435
Epoch 8922/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0057 - accuracy: 1.0000 - val_loss: 8.3035 - val_accuracy: 0.3434
Epoch 8923/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0057 - accuracy: 1.0000 - val_loss: 8.3042 - val_accuracy: 0.3433
Epoch 8924/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0057 - accuracy: 1.0000 - val_loss: 8.3045 - val_accuracy: 0.3434
Epoch 8925/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0057 - accuracy: 1.0000 - val_loss: 8.3048 - val_accuracy: 0.3434
Epoch 8926/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0057 - accuracy: 1.0000 - val_loss: 8.3054 - val_accuracy: 0.3435
Epoch 8927/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0057 - accuracy: 1.0000 - val_loss: 8.3062 - val_accuracy: 0.3434
Epoch 8928/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0057 - accuracy: 1.0000 - val_loss: 8.3071 - val_accuracy: 0.3435
Epoch 8929/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0057 - accuracy: 1.0000 - val_loss: 8.3081 - val_accuracy: 0.3435
Epoch 8930/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0057 - accuracy: 1.0000 - val_loss: 8.3091 - val_accuracy: 0.3435
Epoch 8931/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0057 - accuracy: 1.0000 - val_loss: 8.3101 - val_accuracy: 0.3434
Epoch 8932/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0057 - accuracy: 1.0000 - val_loss: 8.3107 - val_accuracy: 0.3433
Epoch 8933/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0057 - accuracy: 1.0000 - val_loss: 8.3113 - val_accuracy: 0.3433
Epoch 8934/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0057 - accuracy: 1.0000 - val_loss: 8.3119 - val_accuracy: 0.3434
Epoch 8935/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0057 - accuracy: 1.0000 - val_loss: 8.3127 - val_accuracy: 0.3435
Epoch 8936/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0057 - accuracy: 1.0000 - val_loss: 8.3135 - val_accuracy: 0.3434
Epoch 8937/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0057 - accuracy: 1.0000 - val_loss: 8.3143 - val_accuracy: 0.3433
Epoch 8938/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0057 - accuracy: 1.0000 - val_loss: 8.3150 - val_accuracy: 0.3434
Epoch 8939/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0056 - accuracy: 1.0000 - val_loss: 8.3156 - val_accuracy: 0.3434
Epoch 8940/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0056 - accuracy: 1.0000 - val_loss: 8.3164 - val_accuracy: 0.3434
Epoch 8941/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0056 - accuracy: 1.0000 - val_loss: 8.3172 - val_accuracy: 0.3434
Epoch 8942/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0056 - accuracy: 1.0000 - val_loss: 8.3181 - val_accuracy: 0.3434
Epoch 8943/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0056 - accuracy: 1.0000 - val_loss: 8.3189 - val_accuracy: 0.3433
Epoch 8944/10000
1/1 [==============================] - 0s 118ms/step - loss: 0.0056 - accuracy: 1.0000 - val_loss: 8.3197 - val_accuracy: 0.3433
Epoch 8945/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0056 - accuracy: 1.0000 - val_loss: 8.3204 - val_accuracy: 0.3433
Epoch 8946/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0056 - accuracy: 1.0000 - val_loss: 8.3210 - val_accuracy: 0.3435
Epoch 8947/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0056 - accuracy: 1.0000 - val_loss: 8.3215 - val_accuracy: 0.3435
Epoch 8948/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0056 - accuracy: 1.0000 - val_loss: 8.3221 - val_accuracy: 0.3435
Epoch 8949/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0056 - accuracy: 1.0000 - val_loss: 8.3230 - val_accuracy: 0.3436
Epoch 8950/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0056 - accuracy: 1.0000 - val_loss: 8.3238 - val_accuracy: 0.3436
Epoch 8951/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0056 - accuracy: 1.0000 - val_loss: 8.3247 - val_accuracy: 0.3437
Epoch 8952/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0056 - accuracy: 1.0000 - val_loss: 8.3255 - val_accuracy: 0.3436
Epoch 8953/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0056 - accuracy: 1.0000 - val_loss: 8.3261 - val_accuracy: 0.3435
Epoch 8954/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0056 - accuracy: 1.0000 - val_loss: 8.3267 - val_accuracy: 0.3434
Epoch 8955/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0056 - accuracy: 1.0000 - val_loss: 8.3273 - val_accuracy: 0.3435
Epoch 8956/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0056 - accuracy: 1.0000 - val_loss: 8.3281 - val_accuracy: 0.3434
Epoch 8957/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0056 - accuracy: 1.0000 - val_loss: 8.3289 - val_accuracy: 0.3435
Epoch 8958/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0056 - accuracy: 1.0000 - val_loss: 8.3297 - val_accuracy: 0.3434
Epoch 8959/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0056 - accuracy: 1.0000 - val_loss: 8.3305 - val_accuracy: 0.3435
Epoch 8960/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0055 - accuracy: 1.0000 - val_loss: 8.3312 - val_accuracy: 0.3436
Epoch 8961/10000
1/1 [==============================] - 0s 102ms/step - loss: 0.0055 - accuracy: 1.0000 - val_loss: 8.3319 - val_accuracy: 0.3436
Epoch 8962/10000
1/1 [==============================] - 0s 118ms/step - loss: 0.0055 - accuracy: 1.0000 - val_loss: 8.3326 - val_accuracy: 0.3435
Epoch 8963/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0055 - accuracy: 1.0000 - val_loss: 8.3333 - val_accuracy: 0.3435
Epoch 8964/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0055 - accuracy: 1.0000 - val_loss: 8.3339 - val_accuracy: 0.3434
Epoch 8965/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0055 - accuracy: 1.0000 - val_loss: 8.3345 - val_accuracy: 0.3435
Epoch 8966/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0055 - accuracy: 1.0000 - val_loss: 8.3354 - val_accuracy: 0.3434
Epoch 8967/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0055 - accuracy: 1.0000 - val_loss: 8.3363 - val_accuracy: 0.3435
Epoch 8968/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0055 - accuracy: 1.0000 - val_loss: 8.3371 - val_accuracy: 0.3433
Epoch 8969/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0055 - accuracy: 1.0000 - val_loss: 8.3379 - val_accuracy: 0.3437
Epoch 8970/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0055 - accuracy: 1.0000 - val_loss: 8.3387 - val_accuracy: 0.3435
Epoch 8971/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0055 - accuracy: 1.0000 - val_loss: 8.3397 - val_accuracy: 0.3436
Epoch 8972/10000
1/1 [==============================] - 0s 104ms/step - loss: 0.0055 - accuracy: 1.0000 - val_loss: 8.3404 - val_accuracy: 0.3434
Epoch 8973/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0055 - accuracy: 1.0000 - val_loss: 8.3412 - val_accuracy: 0.3433
Epoch 8974/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0055 - accuracy: 1.0000 - val_loss: 8.3419 - val_accuracy: 0.3434
Epoch 8975/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0055 - accuracy: 1.0000 - val_loss: 8.3425 - val_accuracy: 0.3433
Epoch 8976/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0055 - accuracy: 1.0000 - val_loss: 8.3431 - val_accuracy: 0.3433
Epoch 8977/10000
1/1 [==============================] - 0s 102ms/step - loss: 0.0055 - accuracy: 1.0000 - val_loss: 8.3437 - val_accuracy: 0.3434
Epoch 8978/10000
1/1 [==============================] - 0s 104ms/step - loss: 0.0055 - accuracy: 1.0000 - val_loss: 8.3445 - val_accuracy: 0.3434
Epoch 8979/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0055 - accuracy: 1.0000 - val_loss: 8.3453 - val_accuracy: 0.3434
Epoch 8980/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0055 - accuracy: 1.0000 - val_loss: 8.3461 - val_accuracy: 0.3434
Epoch 8981/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0054 - accuracy: 1.0000 - val_loss: 8.3465 - val_accuracy: 0.3433
Epoch 8982/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0054 - accuracy: 1.0000 - val_loss: 8.3469 - val_accuracy: 0.3432
Epoch 8983/10000
1/1 [==============================] - 0s 103ms/step - loss: 0.0054 - accuracy: 1.0000 - val_loss: 8.3475 - val_accuracy: 0.3435
Epoch 8984/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0054 - accuracy: 1.0000 - val_loss: 8.3483 - val_accuracy: 0.3433
Epoch 8985/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0054 - accuracy: 1.0000 - val_loss: 8.3493 - val_accuracy: 0.3432
Epoch 8986/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0054 - accuracy: 1.0000 - val_loss: 8.3502 - val_accuracy: 0.3434
Epoch 8987/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0054 - accuracy: 1.0000 - val_loss: 8.3511 - val_accuracy: 0.3434
Epoch 8988/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0054 - accuracy: 1.0000 - val_loss: 8.3519 - val_accuracy: 0.3433
Epoch 8989/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0054 - accuracy: 1.0000 - val_loss: 8.3525 - val_accuracy: 0.3433
Epoch 8990/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0054 - accuracy: 1.0000 - val_loss: 8.3530 - val_accuracy: 0.3433
Epoch 8991/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0054 - accuracy: 1.0000 - val_loss: 8.3536 - val_accuracy: 0.3434
Epoch 8992/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0054 - accuracy: 1.0000 - val_loss: 8.3543 - val_accuracy: 0.3433
Epoch 8993/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0054 - accuracy: 1.0000 - val_loss: 8.3551 - val_accuracy: 0.3434
Epoch 8994/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0054 - accuracy: 1.0000 - val_loss: 8.3560 - val_accuracy: 0.3431
Epoch 8995/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0054 - accuracy: 1.0000 - val_loss: 8.3569 - val_accuracy: 0.3431
Epoch 8996/10000
1/1 [==============================] - 0s 104ms/step - loss: 0.0054 - accuracy: 1.0000 - val_loss: 8.3578 - val_accuracy: 0.3432
Epoch 8997/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0054 - accuracy: 1.0000 - val_loss: 8.3586 - val_accuracy: 0.3432
Epoch 8998/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0054 - accuracy: 1.0000 - val_loss: 8.3593 - val_accuracy: 0.3434
Epoch 8999/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0054 - accuracy: 1.0000 - val_loss: 8.3598 - val_accuracy: 0.3433
Epoch 9000/10000
1/1 [==============================] - 0s 117ms/step - loss: 0.0054 - accuracy: 1.0000 - val_loss: 8.3604 - val_accuracy: 0.3434
Epoch 9001/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0054 - accuracy: 1.0000 - val_loss: 8.3610 - val_accuracy: 0.3433
Epoch 9002/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0053 - accuracy: 1.0000 - val_loss: 8.3618 - val_accuracy: 0.3432
Epoch 9003/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0053 - accuracy: 1.0000 - val_loss: 8.3625 - val_accuracy: 0.3434
Epoch 9004/10000
1/1 [==============================] - 0s 121ms/step - loss: 0.0053 - accuracy: 1.0000 - val_loss: 8.3633 - val_accuracy: 0.3432
Epoch 9005/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0053 - accuracy: 1.0000 - val_loss: 8.3640 - val_accuracy: 0.3434
Epoch 9006/10000
1/1 [==============================] - 0s 119ms/step - loss: 0.0053 - accuracy: 1.0000 - val_loss: 8.3647 - val_accuracy: 0.3434
Epoch 9007/10000
1/1 [==============================] - 0s 123ms/step - loss: 0.0053 - accuracy: 1.0000 - val_loss: 8.3653 - val_accuracy: 0.3432
Epoch 9008/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0053 - accuracy: 1.0000 - val_loss: 8.3660 - val_accuracy: 0.3434
Epoch 9009/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0053 - accuracy: 1.0000 - val_loss: 8.3667 - val_accuracy: 0.3433
Epoch 9010/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0053 - accuracy: 1.0000 - val_loss: 8.3676 - val_accuracy: 0.3433
Epoch 9011/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0053 - accuracy: 1.0000 - val_loss: 8.3687 - val_accuracy: 0.3432
Epoch 9012/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0053 - accuracy: 1.0000 - val_loss: 8.3695 - val_accuracy: 0.3432
Epoch 9013/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0053 - accuracy: 1.0000 - val_loss: 8.3701 - val_accuracy: 0.3433
Epoch 9014/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0053 - accuracy: 1.0000 - val_loss: 8.3706 - val_accuracy: 0.3433
Epoch 9015/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0053 - accuracy: 1.0000 - val_loss: 8.3713 - val_accuracy: 0.3433
Epoch 9016/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0053 - accuracy: 1.0000 - val_loss: 8.3719 - val_accuracy: 0.3433
Epoch 9017/10000
1/1 [==============================] - 0s 102ms/step - loss: 0.0053 - accuracy: 1.0000 - val_loss: 8.3728 - val_accuracy: 0.3432
Epoch 9018/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0053 - accuracy: 1.0000 - val_loss: 8.3737 - val_accuracy: 0.3431
Epoch 9019/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0053 - accuracy: 1.0000 - val_loss: 8.3746 - val_accuracy: 0.3430
Epoch 9020/10000
1/1 [==============================] - 0s 103ms/step - loss: 0.0053 - accuracy: 1.0000 - val_loss: 8.3752 - val_accuracy: 0.3432
Epoch 9021/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0053 - accuracy: 1.0000 - val_loss: 8.3757 - val_accuracy: 0.3431
Epoch 9022/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0053 - accuracy: 1.0000 - val_loss: 8.3763 - val_accuracy: 0.3432
Epoch 9023/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0053 - accuracy: 1.0000 - val_loss: 8.3770 - val_accuracy: 0.3431
Epoch 9024/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0052 - accuracy: 1.0000 - val_loss: 8.3778 - val_accuracy: 0.3433
Epoch 9025/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0052 - accuracy: 1.0000 - val_loss: 8.3787 - val_accuracy: 0.3432
Epoch 9026/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0052 - accuracy: 1.0000 - val_loss: 8.3794 - val_accuracy: 0.3433
Epoch 9027/10000
1/1 [==============================] - 0s 103ms/step - loss: 0.0052 - accuracy: 1.0000 - val_loss: 8.3801 - val_accuracy: 0.3432
Epoch 9028/10000
1/1 [==============================] - 0s 102ms/step - loss: 0.0052 - accuracy: 1.0000 - val_loss: 8.3809 - val_accuracy: 0.3432
Epoch 9029/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0052 - accuracy: 1.0000 - val_loss: 8.3816 - val_accuracy: 0.3433
Epoch 9030/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0052 - accuracy: 1.0000 - val_loss: 8.3825 - val_accuracy: 0.3433
Epoch 9031/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0052 - accuracy: 1.0000 - val_loss: 8.3832 - val_accuracy: 0.3433
Epoch 9032/10000
1/1 [==============================] - 0s 102ms/step - loss: 0.0052 - accuracy: 1.0000 - val_loss: 8.3838 - val_accuracy: 0.3433
Epoch 9033/10000
1/1 [==============================] - 0s 104ms/step - loss: 0.0052 - accuracy: 1.0000 - val_loss: 8.3846 - val_accuracy: 0.3433
Epoch 9034/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0052 - accuracy: 1.0000 - val_loss: 8.3854 - val_accuracy: 0.3433
Epoch 9035/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0052 - accuracy: 1.0000 - val_loss: 8.3861 - val_accuracy: 0.3433
Epoch 9036/10000
1/1 [==============================] - 0s 118ms/step - loss: 0.0052 - accuracy: 1.0000 - val_loss: 8.3869 - val_accuracy: 0.3433
Epoch 9037/10000
1/1 [==============================] - 0s 118ms/step - loss: 0.0052 - accuracy: 1.0000 - val_loss: 8.3877 - val_accuracy: 0.3433
Epoch 9038/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0052 - accuracy: 1.0000 - val_loss: 8.3885 - val_accuracy: 0.3433
Epoch 9039/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0052 - accuracy: 1.0000 - val_loss: 8.3893 - val_accuracy: 0.3432
Epoch 9040/10000
1/1 [==============================] - 0s 116ms/step - loss: 0.0052 - accuracy: 1.0000 - val_loss: 8.3900 - val_accuracy: 0.3432
Epoch 9041/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0052 - accuracy: 1.0000 - val_loss: 8.3906 - val_accuracy: 0.3434
Epoch 9042/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0052 - accuracy: 1.0000 - val_loss: 8.3911 - val_accuracy: 0.3435
Epoch 9043/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0052 - accuracy: 1.0000 - val_loss: 8.3917 - val_accuracy: 0.3434
Epoch 9044/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0052 - accuracy: 1.0000 - val_loss: 8.3924 - val_accuracy: 0.3435
Epoch 9045/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0052 - accuracy: 1.0000 - val_loss: 8.3931 - val_accuracy: 0.3434
Epoch 9046/10000
1/1 [==============================] - 0s 116ms/step - loss: 0.0051 - accuracy: 1.0000 - val_loss: 8.3939 - val_accuracy: 0.3435
Epoch 9047/10000
1/1 [==============================] - 0s 117ms/step - loss: 0.0051 - accuracy: 1.0000 - val_loss: 8.3947 - val_accuracy: 0.3436
Epoch 9048/10000
1/1 [==============================] - 0s 116ms/step - loss: 0.0051 - accuracy: 1.0000 - val_loss: 8.3955 - val_accuracy: 0.3435
Epoch 9049/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0051 - accuracy: 1.0000 - val_loss: 8.3964 - val_accuracy: 0.3433
Epoch 9050/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0051 - accuracy: 1.0000 - val_loss: 8.3973 - val_accuracy: 0.3435
Epoch 9051/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0051 - accuracy: 1.0000 - val_loss: 8.3981 - val_accuracy: 0.3434
Epoch 9052/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0051 - accuracy: 1.0000 - val_loss: 8.3986 - val_accuracy: 0.3434
Epoch 9053/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0051 - accuracy: 1.0000 - val_loss: 8.3993 - val_accuracy: 0.3435
Epoch 9054/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0051 - accuracy: 1.0000 - val_loss: 8.3999 - val_accuracy: 0.3434
Epoch 9055/10000
1/1 [==============================] - 0s 104ms/step - loss: 0.0051 - accuracy: 1.0000 - val_loss: 8.4007 - val_accuracy: 0.3436
Epoch 9056/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0051 - accuracy: 1.0000 - val_loss: 8.4013 - val_accuracy: 0.3434
Epoch 9057/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0051 - accuracy: 1.0000 - val_loss: 8.4019 - val_accuracy: 0.3435
Epoch 9058/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0051 - accuracy: 1.0000 - val_loss: 8.4026 - val_accuracy: 0.3435
Epoch 9059/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0051 - accuracy: 1.0000 - val_loss: 8.4034 - val_accuracy: 0.3433
Epoch 9060/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0051 - accuracy: 1.0000 - val_loss: 8.4042 - val_accuracy: 0.3434
Epoch 9061/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0051 - accuracy: 1.0000 - val_loss: 8.4051 - val_accuracy: 0.3435
Epoch 9062/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0051 - accuracy: 1.0000 - val_loss: 8.4061 - val_accuracy: 0.3433
Epoch 9063/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0051 - accuracy: 1.0000 - val_loss: 8.4069 - val_accuracy: 0.3433
Epoch 9064/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0051 - accuracy: 1.0000 - val_loss: 8.4076 - val_accuracy: 0.3433
Epoch 9065/10000
1/1 [==============================] - 0s 104ms/step - loss: 0.0051 - accuracy: 1.0000 - val_loss: 8.4081 - val_accuracy: 0.3435
Epoch 9066/10000
1/1 [==============================] - 0s 104ms/step - loss: 0.0051 - accuracy: 1.0000 - val_loss: 8.4088 - val_accuracy: 0.3436
Epoch 9067/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0051 - accuracy: 1.0000 - val_loss: 8.4094 - val_accuracy: 0.3436
Epoch 9068/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0051 - accuracy: 1.0000 - val_loss: 8.4101 - val_accuracy: 0.3434
Epoch 9069/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0050 - accuracy: 1.0000 - val_loss: 8.4109 - val_accuracy: 0.3436
Epoch 9070/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0050 - accuracy: 1.0000 - val_loss: 8.4115 - val_accuracy: 0.3437
Epoch 9071/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0050 - accuracy: 1.0000 - val_loss: 8.4122 - val_accuracy: 0.3436
Epoch 9072/10000
1/1 [==============================] - 0s 104ms/step - loss: 0.0050 - accuracy: 1.0000 - val_loss: 8.4131 - val_accuracy: 0.3435
Epoch 9073/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0050 - accuracy: 1.0000 - val_loss: 8.4139 - val_accuracy: 0.3436
Epoch 9074/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0050 - accuracy: 1.0000 - val_loss: 8.4147 - val_accuracy: 0.3435
Epoch 9075/10000
1/1 [==============================] - 0s 104ms/step - loss: 0.0050 - accuracy: 1.0000 - val_loss: 8.4154 - val_accuracy: 0.3437
Epoch 9076/10000
1/1 [==============================] - 0s 103ms/step - loss: 0.0050 - accuracy: 1.0000 - val_loss: 8.4161 - val_accuracy: 0.3435
Epoch 9077/10000
1/1 [==============================] - 0s 103ms/step - loss: 0.0050 - accuracy: 1.0000 - val_loss: 8.4167 - val_accuracy: 0.3436
Epoch 9078/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0050 - accuracy: 1.0000 - val_loss: 8.4172 - val_accuracy: 0.3437
Epoch 9079/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0050 - accuracy: 1.0000 - val_loss: 8.4179 - val_accuracy: 0.3438
Epoch 9080/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0050 - accuracy: 1.0000 - val_loss: 8.4185 - val_accuracy: 0.3437
Epoch 9081/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0050 - accuracy: 1.0000 - val_loss: 8.4193 - val_accuracy: 0.3435
Epoch 9082/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0050 - accuracy: 1.0000 - val_loss: 8.4200 - val_accuracy: 0.3437
Epoch 9083/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0050 - accuracy: 1.0000 - val_loss: 8.4207 - val_accuracy: 0.3437
Epoch 9084/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0050 - accuracy: 1.0000 - val_loss: 8.4215 - val_accuracy: 0.3438
Epoch 9085/10000
1/1 [==============================] - 0s 104ms/step - loss: 0.0050 - accuracy: 1.0000 - val_loss: 8.4224 - val_accuracy: 0.3436
Epoch 9086/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0050 - accuracy: 1.0000 - val_loss: 8.4233 - val_accuracy: 0.3439
Epoch 9087/10000
1/1 [==============================] - 0s 104ms/step - loss: 0.0050 - accuracy: 1.0000 - val_loss: 8.4242 - val_accuracy: 0.3437
Epoch 9088/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0050 - accuracy: 1.0000 - val_loss: 8.4249 - val_accuracy: 0.3438
Epoch 9089/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0050 - accuracy: 1.0000 - val_loss: 8.4256 - val_accuracy: 0.3439
Epoch 9090/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0050 - accuracy: 1.0000 - val_loss: 8.4261 - val_accuracy: 0.3437
Epoch 9091/10000
1/1 [==============================] - 0s 103ms/step - loss: 0.0050 - accuracy: 1.0000 - val_loss: 8.4267 - val_accuracy: 0.3436
Epoch 9092/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0050 - accuracy: 1.0000 - val_loss: 8.4273 - val_accuracy: 0.3438
Epoch 9093/10000
1/1 [==============================] - 0s 103ms/step - loss: 0.0049 - accuracy: 1.0000 - val_loss: 8.4280 - val_accuracy: 0.3436
Epoch 9094/10000
1/1 [==============================] - 0s 117ms/step - loss: 0.0049 - accuracy: 1.0000 - val_loss: 8.4289 - val_accuracy: 0.3437
Epoch 9095/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0049 - accuracy: 1.0000 - val_loss: 8.4298 - val_accuracy: 0.3438
Epoch 9096/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0049 - accuracy: 1.0000 - val_loss: 8.4304 - val_accuracy: 0.3438
Epoch 9097/10000
1/1 [==============================] - 0s 100ms/step - loss: 0.0049 - accuracy: 1.0000 - val_loss: 8.4310 - val_accuracy: 0.3439
Epoch 9098/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0049 - accuracy: 1.0000 - val_loss: 8.4317 - val_accuracy: 0.3438
Epoch 9099/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0049 - accuracy: 1.0000 - val_loss: 8.4324 - val_accuracy: 0.3439
Epoch 9100/10000
1/1 [==============================] - 0s 104ms/step - loss: 0.0049 - accuracy: 1.0000 - val_loss: 8.4332 - val_accuracy: 0.3437
Epoch 9101/10000
1/1 [==============================] - 0s 102ms/step - loss: 0.0049 - accuracy: 1.0000 - val_loss: 8.4339 - val_accuracy: 0.3440
Epoch 9102/10000
1/1 [==============================] - 0s 101ms/step - loss: 0.0049 - accuracy: 1.0000 - val_loss: 8.4346 - val_accuracy: 0.3439
Epoch 9103/10000
1/1 [==============================] - 0s 100ms/step - loss: 0.0049 - accuracy: 1.0000 - val_loss: 8.4352 - val_accuracy: 0.3437
Epoch 9104/10000
1/1 [==============================] - 0s 102ms/step - loss: 0.0049 - accuracy: 1.0000 - val_loss: 8.4358 - val_accuracy: 0.3440
Epoch 9105/10000
1/1 [==============================] - 0s 116ms/step - loss: 0.0049 - accuracy: 1.0000 - val_loss: 8.4365 - val_accuracy: 0.3439
Epoch 9106/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0049 - accuracy: 1.0000 - val_loss: 8.4374 - val_accuracy: 0.3438
Epoch 9107/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0049 - accuracy: 1.0000 - val_loss: 8.4382 - val_accuracy: 0.3439
Epoch 9108/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0049 - accuracy: 1.0000 - val_loss: 8.4391 - val_accuracy: 0.3439
Epoch 9109/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0049 - accuracy: 1.0000 - val_loss: 8.4399 - val_accuracy: 0.3436
Epoch 9110/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0049 - accuracy: 1.0000 - val_loss: 8.4405 - val_accuracy: 0.3439
Epoch 9111/10000
1/1 [==============================] - 0s 119ms/step - loss: 0.0049 - accuracy: 1.0000 - val_loss: 8.4410 - val_accuracy: 0.3438
Epoch 9112/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0049 - accuracy: 1.0000 - val_loss: 8.4416 - val_accuracy: 0.3438
Epoch 9113/10000
1/1 [==============================] - 0s 116ms/step - loss: 0.0049 - accuracy: 1.0000 - val_loss: 8.4423 - val_accuracy: 0.3439
Epoch 9114/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0049 - accuracy: 1.0000 - val_loss: 8.4431 - val_accuracy: 0.3439
Epoch 9115/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0049 - accuracy: 1.0000 - val_loss: 8.4439 - val_accuracy: 0.3439
Epoch 9116/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0049 - accuracy: 1.0000 - val_loss: 8.4449 - val_accuracy: 0.3439
Epoch 9117/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0048 - accuracy: 1.0000 - val_loss: 8.4455 - val_accuracy: 0.3437
Epoch 9118/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0048 - accuracy: 1.0000 - val_loss: 8.4462 - val_accuracy: 0.3440
Epoch 9119/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0048 - accuracy: 1.0000 - val_loss: 8.4467 - val_accuracy: 0.3439
Epoch 9120/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0048 - accuracy: 1.0000 - val_loss: 8.4473 - val_accuracy: 0.3440
Epoch 9121/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0048 - accuracy: 1.0000 - val_loss: 8.4480 - val_accuracy: 0.3440
Epoch 9122/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0048 - accuracy: 1.0000 - val_loss: 8.4490 - val_accuracy: 0.3438
Epoch 9123/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0048 - accuracy: 1.0000 - val_loss: 8.4499 - val_accuracy: 0.3440
Epoch 9124/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0048 - accuracy: 1.0000 - val_loss: 8.4508 - val_accuracy: 0.3439
Epoch 9125/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0048 - accuracy: 1.0000 - val_loss: 8.4513 - val_accuracy: 0.3440
Epoch 9126/10000
1/1 [==============================] - 0s 104ms/step - loss: 0.0048 - accuracy: 1.0000 - val_loss: 8.4517 - val_accuracy: 0.3439
Epoch 9127/10000
1/1 [==============================] - 0s 103ms/step - loss: 0.0048 - accuracy: 1.0000 - val_loss: 8.4522 - val_accuracy: 0.3439
Epoch 9128/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0048 - accuracy: 1.0000 - val_loss: 8.4530 - val_accuracy: 0.3439
Epoch 9129/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0048 - accuracy: 1.0000 - val_loss: 8.4539 - val_accuracy: 0.3438
Epoch 9130/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0048 - accuracy: 1.0000 - val_loss: 8.4548 - val_accuracy: 0.3439
Epoch 9131/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0048 - accuracy: 1.0000 - val_loss: 8.4555 - val_accuracy: 0.3439
Epoch 9132/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0048 - accuracy: 1.0000 - val_loss: 8.4562 - val_accuracy: 0.3439
Epoch 9133/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0048 - accuracy: 1.0000 - val_loss: 8.4567 - val_accuracy: 0.3439
Epoch 9134/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0048 - accuracy: 1.0000 - val_loss: 8.4574 - val_accuracy: 0.3439
Epoch 9135/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0048 - accuracy: 1.0000 - val_loss: 8.4581 - val_accuracy: 0.3439
Epoch 9136/10000
1/1 [==============================] - 0s 104ms/step - loss: 0.0048 - accuracy: 1.0000 - val_loss: 8.4588 - val_accuracy: 0.3440
Epoch 9137/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0048 - accuracy: 1.0000 - val_loss: 8.4596 - val_accuracy: 0.3440
Epoch 9138/10000
1/1 [==============================] - 0s 104ms/step - loss: 0.0048 - accuracy: 1.0000 - val_loss: 8.4604 - val_accuracy: 0.3439
Epoch 9139/10000
1/1 [==============================] - 0s 102ms/step - loss: 0.0048 - accuracy: 1.0000 - val_loss: 8.4611 - val_accuracy: 0.3438
Epoch 9140/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0048 - accuracy: 1.0000 - val_loss: 8.4617 - val_accuracy: 0.3439
Epoch 9141/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0048 - accuracy: 1.0000 - val_loss: 8.4622 - val_accuracy: 0.3438
Epoch 9142/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0047 - accuracy: 1.0000 - val_loss: 8.4627 - val_accuracy: 0.3439
Epoch 9143/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0047 - accuracy: 1.0000 - val_loss: 8.4633 - val_accuracy: 0.3440
Epoch 9144/10000
1/1 [==============================] - 0s 102ms/step - loss: 0.0047 - accuracy: 1.0000 - val_loss: 8.4641 - val_accuracy: 0.3440
Epoch 9145/10000
1/1 [==============================] - 0s 104ms/step - loss: 0.0047 - accuracy: 1.0000 - val_loss: 8.4649 - val_accuracy: 0.3439
Epoch 9146/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0047 - accuracy: 1.0000 - val_loss: 8.4658 - val_accuracy: 0.3439
Epoch 9147/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0047 - accuracy: 1.0000 - val_loss: 8.4667 - val_accuracy: 0.3439
Epoch 9148/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0047 - accuracy: 1.0000 - val_loss: 8.4674 - val_accuracy: 0.3439
Epoch 9149/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0047 - accuracy: 1.0000 - val_loss: 8.4681 - val_accuracy: 0.3439
Epoch 9150/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0047 - accuracy: 1.0000 - val_loss: 8.4689 - val_accuracy: 0.3438
Epoch 9151/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0047 - accuracy: 1.0000 - val_loss: 8.4696 - val_accuracy: 0.3440
Epoch 9152/10000
1/1 [==============================] - 0s 104ms/step - loss: 0.0047 - accuracy: 1.0000 - val_loss: 8.4702 - val_accuracy: 0.3441
Epoch 9153/10000
1/1 [==============================] - 0s 104ms/step - loss: 0.0047 - accuracy: 1.0000 - val_loss: 8.4709 - val_accuracy: 0.3439
Epoch 9154/10000
1/1 [==============================] - 0s 104ms/step - loss: 0.0047 - accuracy: 1.0000 - val_loss: 8.4717 - val_accuracy: 0.3439
Epoch 9155/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0047 - accuracy: 1.0000 - val_loss: 8.4724 - val_accuracy: 0.3438
Epoch 9156/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0047 - accuracy: 1.0000 - val_loss: 8.4732 - val_accuracy: 0.3441
Epoch 9157/10000
1/1 [==============================] - 0s 104ms/step - loss: 0.0047 - accuracy: 1.0000 - val_loss: 8.4739 - val_accuracy: 0.3440
Epoch 9158/10000
1/1 [==============================] - 0s 104ms/step - loss: 0.0047 - accuracy: 1.0000 - val_loss: 8.4746 - val_accuracy: 0.3439
Epoch 9159/10000
1/1 [==============================] - 0s 117ms/step - loss: 0.0047 - accuracy: 1.0000 - val_loss: 8.4753 - val_accuracy: 0.3439
Epoch 9160/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0047 - accuracy: 1.0000 - val_loss: 8.4761 - val_accuracy: 0.3438
Epoch 9161/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0047 - accuracy: 1.0000 - val_loss: 8.4767 - val_accuracy: 0.3440
Epoch 9162/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0047 - accuracy: 1.0000 - val_loss: 8.4775 - val_accuracy: 0.3441
Epoch 9163/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0047 - accuracy: 1.0000 - val_loss: 8.4782 - val_accuracy: 0.3440
Epoch 9164/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0047 - accuracy: 1.0000 - val_loss: 8.4788 - val_accuracy: 0.3441
Epoch 9165/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0047 - accuracy: 1.0000 - val_loss: 8.4793 - val_accuracy: 0.3439
Epoch 9166/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0047 - accuracy: 1.0000 - val_loss: 8.4800 - val_accuracy: 0.3440
Epoch 9167/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0046 - accuracy: 1.0000 - val_loss: 8.4806 - val_accuracy: 0.3440
Epoch 9168/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0046 - accuracy: 1.0000 - val_loss: 8.4813 - val_accuracy: 0.3440
Epoch 9169/10000
1/1 [==============================] - 0s 104ms/step - loss: 0.0046 - accuracy: 1.0000 - val_loss: 8.4820 - val_accuracy: 0.3438
Epoch 9170/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0046 - accuracy: 1.0000 - val_loss: 8.4827 - val_accuracy: 0.3440
Epoch 9171/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0046 - accuracy: 1.0000 - val_loss: 8.4835 - val_accuracy: 0.3441
Epoch 9172/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0046 - accuracy: 1.0000 - val_loss: 8.4842 - val_accuracy: 0.3441
Epoch 9173/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0046 - accuracy: 1.0000 - val_loss: 8.4849 - val_accuracy: 0.3441
Epoch 9174/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0046 - accuracy: 1.0000 - val_loss: 8.4857 - val_accuracy: 0.3441
Epoch 9175/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0046 - accuracy: 1.0000 - val_loss: 8.4864 - val_accuracy: 0.3441
Epoch 9176/10000
1/1 [==============================] - 0s 102ms/step - loss: 0.0046 - accuracy: 1.0000 - val_loss: 8.4870 - val_accuracy: 0.3441
Epoch 9177/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0046 - accuracy: 1.0000 - val_loss: 8.4878 - val_accuracy: 0.3440
Epoch 9178/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0046 - accuracy: 1.0000 - val_loss: 8.4885 - val_accuracy: 0.3440
Epoch 9179/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0046 - accuracy: 1.0000 - val_loss: 8.4893 - val_accuracy: 0.3439
Epoch 9180/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0046 - accuracy: 1.0000 - val_loss: 8.4900 - val_accuracy: 0.3440
Epoch 9181/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0046 - accuracy: 1.0000 - val_loss: 8.4906 - val_accuracy: 0.3439
Epoch 9182/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0046 - accuracy: 1.0000 - val_loss: 8.4913 - val_accuracy: 0.3439
Epoch 9183/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0046 - accuracy: 1.0000 - val_loss: 8.4920 - val_accuracy: 0.3440
Epoch 9184/10000
1/1 [==============================] - 0s 104ms/step - loss: 0.0046 - accuracy: 1.0000 - val_loss: 8.4927 - val_accuracy: 0.3439
Epoch 9185/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0046 - accuracy: 1.0000 - val_loss: 8.4936 - val_accuracy: 0.3441
Epoch 9186/10000
1/1 [==============================] - 0s 104ms/step - loss: 0.0046 - accuracy: 1.0000 - val_loss: 8.4945 - val_accuracy: 0.3441
Epoch 9187/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0046 - accuracy: 1.0000 - val_loss: 8.4950 - val_accuracy: 0.3440
Epoch 9188/10000
1/1 [==============================] - 0s 103ms/step - loss: 0.0046 - accuracy: 1.0000 - val_loss: 8.4955 - val_accuracy: 0.3440
Epoch 9189/10000
1/1 [==============================] - 0s 104ms/step - loss: 0.0046 - accuracy: 1.0000 - val_loss: 8.4961 - val_accuracy: 0.3440
Epoch 9190/10000
1/1 [==============================] - 0s 117ms/step - loss: 0.0046 - accuracy: 1.0000 - val_loss: 8.4967 - val_accuracy: 0.3440
Epoch 9191/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0046 - accuracy: 1.0000 - val_loss: 8.4975 - val_accuracy: 0.3440
Epoch 9192/10000
1/1 [==============================] - 0s 101ms/step - loss: 0.0046 - accuracy: 1.0000 - val_loss: 8.4983 - val_accuracy: 0.3439
Epoch 9193/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0045 - accuracy: 1.0000 - val_loss: 8.4991 - val_accuracy: 0.3440
Epoch 9194/10000
1/1 [==============================] - 0s 104ms/step - loss: 0.0045 - accuracy: 1.0000 - val_loss: 8.4999 - val_accuracy: 0.3440
Epoch 9195/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0045 - accuracy: 1.0000 - val_loss: 8.5007 - val_accuracy: 0.3440
Epoch 9196/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0045 - accuracy: 1.0000 - val_loss: 8.5012 - val_accuracy: 0.3440
Epoch 9197/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0045 - accuracy: 1.0000 - val_loss: 8.5019 - val_accuracy: 0.3440
Epoch 9198/10000
1/1 [==============================] - 0s 104ms/step - loss: 0.0045 - accuracy: 1.0000 - val_loss: 8.5026 - val_accuracy: 0.3440
Epoch 9199/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0045 - accuracy: 1.0000 - val_loss: 8.5033 - val_accuracy: 0.3440
Epoch 9200/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0045 - accuracy: 1.0000 - val_loss: 8.5040 - val_accuracy: 0.3440
Epoch 9201/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0045 - accuracy: 1.0000 - val_loss: 8.5048 - val_accuracy: 0.3440
Epoch 9202/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0045 - accuracy: 1.0000 - val_loss: 8.5055 - val_accuracy: 0.3439
Epoch 9203/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0045 - accuracy: 1.0000 - val_loss: 8.5061 - val_accuracy: 0.3440
Epoch 9204/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0045 - accuracy: 1.0000 - val_loss: 8.5068 - val_accuracy: 0.3439
Epoch 9205/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0045 - accuracy: 1.0000 - val_loss: 8.5076 - val_accuracy: 0.3439
Epoch 9206/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0045 - accuracy: 1.0000 - val_loss: 8.5085 - val_accuracy: 0.3439
Epoch 9207/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0045 - accuracy: 1.0000 - val_loss: 8.5093 - val_accuracy: 0.3439
Epoch 9208/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0045 - accuracy: 1.0000 - val_loss: 8.5101 - val_accuracy: 0.3440
Epoch 9209/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0045 - accuracy: 1.0000 - val_loss: 8.5108 - val_accuracy: 0.3440
Epoch 9210/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0045 - accuracy: 1.0000 - val_loss: 8.5113 - val_accuracy: 0.3440
Epoch 9211/10000
1/1 [==============================] - 0s 104ms/step - loss: 0.0045 - accuracy: 1.0000 - val_loss: 8.5118 - val_accuracy: 0.3440
Epoch 9212/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0045 - accuracy: 1.0000 - val_loss: 8.5124 - val_accuracy: 0.3439
Epoch 9213/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0045 - accuracy: 1.0000 - val_loss: 8.5131 - val_accuracy: 0.3440
Epoch 9214/10000
1/1 [==============================] - 0s 125ms/step - loss: 0.0045 - accuracy: 1.0000 - val_loss: 8.5139 - val_accuracy: 0.3440
Epoch 9215/10000
1/1 [==============================] - 0s 116ms/step - loss: 0.0045 - accuracy: 1.0000 - val_loss: 8.5146 - val_accuracy: 0.3441
Epoch 9216/10000
1/1 [==============================] - 0s 124ms/step - loss: 0.0045 - accuracy: 1.0000 - val_loss: 8.5154 - val_accuracy: 0.3441
Epoch 9217/10000
1/1 [==============================] - 0s 131ms/step - loss: 0.0045 - accuracy: 1.0000 - val_loss: 8.5161 - val_accuracy: 0.3441
Epoch 9218/10000
1/1 [==============================] - 0s 116ms/step - loss: 0.0045 - accuracy: 1.0000 - val_loss: 8.5168 - val_accuracy: 0.3441
Epoch 9219/10000
1/1 [==============================] - 0s 122ms/step - loss: 0.0045 - accuracy: 1.0000 - val_loss: 8.5173 - val_accuracy: 0.3441
Epoch 9220/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0044 - accuracy: 1.0000 - val_loss: 8.5180 - val_accuracy: 0.3441
Epoch 9221/10000
1/1 [==============================] - 0s 123ms/step - loss: 0.0044 - accuracy: 1.0000 - val_loss: 8.5187 - val_accuracy: 0.3441
Epoch 9222/10000
1/1 [==============================] - 0s 123ms/step - loss: 0.0044 - accuracy: 1.0000 - val_loss: 8.5194 - val_accuracy: 0.3440
Epoch 9223/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0044 - accuracy: 1.0000 - val_loss: 8.5203 - val_accuracy: 0.3441
Epoch 9224/10000
1/1 [==============================] - 0s 119ms/step - loss: 0.0044 - accuracy: 1.0000 - val_loss: 8.5212 - val_accuracy: 0.3441
Epoch 9225/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0044 - accuracy: 1.0000 - val_loss: 8.5218 - val_accuracy: 0.3441
Epoch 9226/10000
1/1 [==============================] - 0s 117ms/step - loss: 0.0044 - accuracy: 1.0000 - val_loss: 8.5225 - val_accuracy: 0.3441
Epoch 9227/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0044 - accuracy: 1.0000 - val_loss: 8.5232 - val_accuracy: 0.3441
Epoch 9228/10000
1/1 [==============================] - 0s 125ms/step - loss: 0.0044 - accuracy: 1.0000 - val_loss: 8.5238 - val_accuracy: 0.3440
Epoch 9229/10000
1/1 [==============================] - 0s 124ms/step - loss: 0.0044 - accuracy: 1.0000 - val_loss: 8.5245 - val_accuracy: 0.3441
Epoch 9230/10000
1/1 [==============================] - 0s 119ms/step - loss: 0.0044 - accuracy: 1.0000 - val_loss: 8.5252 - val_accuracy: 0.3441
Epoch 9231/10000
1/1 [==============================] - 0s 116ms/step - loss: 0.0044 - accuracy: 1.0000 - val_loss: 8.5260 - val_accuracy: 0.3441
Epoch 9232/10000
1/1 [==============================] - 0s 116ms/step - loss: 0.0044 - accuracy: 1.0000 - val_loss: 8.5267 - val_accuracy: 0.3441
Epoch 9233/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0044 - accuracy: 1.0000 - val_loss: 8.5274 - val_accuracy: 0.3441
Epoch 9234/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0044 - accuracy: 1.0000 - val_loss: 8.5282 - val_accuracy: 0.3441
Epoch 9235/10000
1/1 [==============================] - 0s 99ms/step - loss: 0.0044 - accuracy: 1.0000 - val_loss: 8.5289 - val_accuracy: 0.3441
Epoch 9236/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0044 - accuracy: 1.0000 - val_loss: 8.5296 - val_accuracy: 0.3441
Epoch 9237/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0044 - accuracy: 1.0000 - val_loss: 8.5304 - val_accuracy: 0.3441
Epoch 9238/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0044 - accuracy: 1.0000 - val_loss: 8.5311 - val_accuracy: 0.3441
Epoch 9239/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0044 - accuracy: 1.0000 - val_loss: 8.5318 - val_accuracy: 0.3441
Epoch 9240/10000
1/1 [==============================] - 0s 103ms/step - loss: 0.0044 - accuracy: 1.0000 - val_loss: 8.5323 - val_accuracy: 0.3441
Epoch 9241/10000
1/1 [==============================] - 0s 102ms/step - loss: 0.0044 - accuracy: 1.0000 - val_loss: 8.5327 - val_accuracy: 0.3441
Epoch 9242/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0044 - accuracy: 1.0000 - val_loss: 8.5333 - val_accuracy: 0.3441
Epoch 9243/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0044 - accuracy: 1.0000 - val_loss: 8.5340 - val_accuracy: 0.3441
Epoch 9244/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0044 - accuracy: 1.0000 - val_loss: 8.5349 - val_accuracy: 0.3441
Epoch 9245/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0044 - accuracy: 1.0000 - val_loss: 8.5358 - val_accuracy: 0.3441
Epoch 9246/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0044 - accuracy: 1.0000 - val_loss: 8.5366 - val_accuracy: 0.3441
Epoch 9247/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0043 - accuracy: 1.0000 - val_loss: 8.5373 - val_accuracy: 0.3441
Epoch 9248/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0043 - accuracy: 1.0000 - val_loss: 8.5379 - val_accuracy: 0.3442
Epoch 9249/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0043 - accuracy: 1.0000 - val_loss: 8.5385 - val_accuracy: 0.3442
Epoch 9250/10000
1/1 [==============================] - 0s 103ms/step - loss: 0.0043 - accuracy: 1.0000 - val_loss: 8.5392 - val_accuracy: 0.3442
Epoch 9251/10000
1/1 [==============================] - 0s 104ms/step - loss: 0.0043 - accuracy: 1.0000 - val_loss: 8.5399 - val_accuracy: 0.3442
Epoch 9252/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0043 - accuracy: 1.0000 - val_loss: 8.5406 - val_accuracy: 0.3442
Epoch 9253/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0043 - accuracy: 1.0000 - val_loss: 8.5414 - val_accuracy: 0.3441
Epoch 9254/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0043 - accuracy: 1.0000 - val_loss: 8.5422 - val_accuracy: 0.3443
Epoch 9255/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0043 - accuracy: 1.0000 - val_loss: 8.5429 - val_accuracy: 0.3442
Epoch 9256/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0043 - accuracy: 1.0000 - val_loss: 8.5435 - val_accuracy: 0.3441
Epoch 9257/10000
1/1 [==============================] - 0s 104ms/step - loss: 0.0043 - accuracy: 1.0000 - val_loss: 8.5440 - val_accuracy: 0.3441
Epoch 9258/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0043 - accuracy: 1.0000 - val_loss: 8.5447 - val_accuracy: 0.3442
Epoch 9259/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0043 - accuracy: 1.0000 - val_loss: 8.5455 - val_accuracy: 0.3441
Epoch 9260/10000
1/1 [==============================] - 0s 104ms/step - loss: 0.0043 - accuracy: 1.0000 - val_loss: 8.5464 - val_accuracy: 0.3441
Epoch 9261/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0043 - accuracy: 1.0000 - val_loss: 8.5472 - val_accuracy: 0.3441
Epoch 9262/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0043 - accuracy: 1.0000 - val_loss: 8.5479 - val_accuracy: 0.3441
Epoch 9263/10000
1/1 [==============================] - 0s 100ms/step - loss: 0.0043 - accuracy: 1.0000 - val_loss: 8.5485 - val_accuracy: 0.3442
Epoch 9264/10000
1/1 [==============================] - 0s 104ms/step - loss: 0.0043 - accuracy: 1.0000 - val_loss: 8.5489 - val_accuracy: 0.3442
Epoch 9265/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0043 - accuracy: 1.0000 - val_loss: 8.5496 - val_accuracy: 0.3442
Epoch 9266/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0043 - accuracy: 1.0000 - val_loss: 8.5504 - val_accuracy: 0.3442
Epoch 9267/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0043 - accuracy: 1.0000 - val_loss: 8.5512 - val_accuracy: 0.3442
Epoch 9268/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0043 - accuracy: 1.0000 - val_loss: 8.5520 - val_accuracy: 0.3441
Epoch 9269/10000
1/1 [==============================] - 0s 103ms/step - loss: 0.0043 - accuracy: 1.0000 - val_loss: 8.5526 - val_accuracy: 0.3441
Epoch 9270/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0043 - accuracy: 1.0000 - val_loss: 8.5531 - val_accuracy: 0.3442
Epoch 9271/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0043 - accuracy: 1.0000 - val_loss: 8.5536 - val_accuracy: 0.3441
Epoch 9272/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0043 - accuracy: 1.0000 - val_loss: 8.5544 - val_accuracy: 0.3441
Epoch 9273/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0043 - accuracy: 1.0000 - val_loss: 8.5552 - val_accuracy: 0.3441
Epoch 9274/10000
1/1 [==============================] - 0s 102ms/step - loss: 0.0043 - accuracy: 1.0000 - val_loss: 8.5561 - val_accuracy: 0.3442
Epoch 9275/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0042 - accuracy: 1.0000 - val_loss: 8.5571 - val_accuracy: 0.3442
Epoch 9276/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0042 - accuracy: 1.0000 - val_loss: 8.5579 - val_accuracy: 0.3441
Epoch 9277/10000
1/1 [==============================] - 0s 103ms/step - loss: 0.0042 - accuracy: 1.0000 - val_loss: 8.5583 - val_accuracy: 0.3441
Epoch 9278/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0042 - accuracy: 1.0000 - val_loss: 8.5587 - val_accuracy: 0.3442
Epoch 9279/10000
1/1 [==============================] - 0s 104ms/step - loss: 0.0042 - accuracy: 1.0000 - val_loss: 8.5591 - val_accuracy: 0.3442
Epoch 9280/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0042 - accuracy: 1.0000 - val_loss: 8.5597 - val_accuracy: 0.3442
Epoch 9281/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0042 - accuracy: 1.0000 - val_loss: 8.5605 - val_accuracy: 0.3442
Epoch 9282/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0042 - accuracy: 1.0000 - val_loss: 8.5613 - val_accuracy: 0.3442
Epoch 9283/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0042 - accuracy: 1.0000 - val_loss: 8.5622 - val_accuracy: 0.3442
Epoch 9284/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0042 - accuracy: 1.0000 - val_loss: 8.5630 - val_accuracy: 0.3442
Epoch 9285/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0042 - accuracy: 1.0000 - val_loss: 8.5636 - val_accuracy: 0.3441
Epoch 9286/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0042 - accuracy: 1.0000 - val_loss: 8.5641 - val_accuracy: 0.3442
Epoch 9287/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0042 - accuracy: 1.0000 - val_loss: 8.5647 - val_accuracy: 0.3442
Epoch 9288/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0042 - accuracy: 1.0000 - val_loss: 8.5654 - val_accuracy: 0.3443
Epoch 9289/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0042 - accuracy: 1.0000 - val_loss: 8.5663 - val_accuracy: 0.3443
Epoch 9290/10000
1/1 [==============================] - 0s 102ms/step - loss: 0.0042 - accuracy: 1.0000 - val_loss: 8.5672 - val_accuracy: 0.3443
Epoch 9291/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0042 - accuracy: 1.0000 - val_loss: 8.5680 - val_accuracy: 0.3442
Epoch 9292/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0042 - accuracy: 1.0000 - val_loss: 8.5687 - val_accuracy: 0.3443
Epoch 9293/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0042 - accuracy: 1.0000 - val_loss: 8.5693 - val_accuracy: 0.3442
Epoch 9294/10000
1/1 [==============================] - 0s 103ms/step - loss: 0.0042 - accuracy: 1.0000 - val_loss: 8.5699 - val_accuracy: 0.3442
Epoch 9295/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0042 - accuracy: 1.0000 - val_loss: 8.5703 - val_accuracy: 0.3442
Epoch 9296/10000
1/1 [==============================] - 0s 103ms/step - loss: 0.0042 - accuracy: 1.0000 - val_loss: 8.5709 - val_accuracy: 0.3442
Epoch 9297/10000
1/1 [==============================] - 0s 102ms/step - loss: 0.0042 - accuracy: 1.0000 - val_loss: 8.5715 - val_accuracy: 0.3443
Epoch 9298/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0042 - accuracy: 1.0000 - val_loss: 8.5723 - val_accuracy: 0.3443
Epoch 9299/10000
1/1 [==============================] - 0s 104ms/step - loss: 0.0042 - accuracy: 1.0000 - val_loss: 8.5732 - val_accuracy: 0.3443
Epoch 9300/10000
1/1 [==============================] - 0s 101ms/step - loss: 0.0042 - accuracy: 1.0000 - val_loss: 8.5740 - val_accuracy: 0.3443
Epoch 9301/10000
1/1 [==============================] - 0s 103ms/step - loss: 0.0042 - accuracy: 1.0000 - val_loss: 8.5748 - val_accuracy: 0.3443
Epoch 9302/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0042 - accuracy: 1.0000 - val_loss: 8.5755 - val_accuracy: 0.3443
Epoch 9303/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0042 - accuracy: 1.0000 - val_loss: 8.5761 - val_accuracy: 0.3443
Epoch 9304/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0042 - accuracy: 1.0000 - val_loss: 8.5769 - val_accuracy: 0.3442
Epoch 9305/10000
1/1 [==============================] - 0s 102ms/step - loss: 0.0041 - accuracy: 1.0000 - val_loss: 8.5774 - val_accuracy: 0.3443
Epoch 9306/10000
1/1 [==============================] - 0s 100ms/step - loss: 0.0041 - accuracy: 1.0000 - val_loss: 8.5780 - val_accuracy: 0.3443
Epoch 9307/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0041 - accuracy: 1.0000 - val_loss: 8.5787 - val_accuracy: 0.3444
Epoch 9308/10000
1/1 [==============================] - 0s 104ms/step - loss: 0.0041 - accuracy: 1.0000 - val_loss: 8.5793 - val_accuracy: 0.3443
Epoch 9309/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0041 - accuracy: 1.0000 - val_loss: 8.5800 - val_accuracy: 0.3444
Epoch 9310/10000
1/1 [==============================] - 0s 104ms/step - loss: 0.0041 - accuracy: 1.0000 - val_loss: 8.5806 - val_accuracy: 0.3443
Epoch 9311/10000
1/1 [==============================] - 0s 103ms/step - loss: 0.0041 - accuracy: 1.0000 - val_loss: 8.5814 - val_accuracy: 0.3444
Epoch 9312/10000
1/1 [==============================] - 0s 104ms/step - loss: 0.0041 - accuracy: 1.0000 - val_loss: 8.5821 - val_accuracy: 0.3445
Epoch 9313/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0041 - accuracy: 1.0000 - val_loss: 8.5828 - val_accuracy: 0.3443
Epoch 9314/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0041 - accuracy: 1.0000 - val_loss: 8.5836 - val_accuracy: 0.3444
Epoch 9315/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0041 - accuracy: 1.0000 - val_loss: 8.5843 - val_accuracy: 0.3444
Epoch 9316/10000
1/1 [==============================] - 0s 104ms/step - loss: 0.0041 - accuracy: 1.0000 - val_loss: 8.5849 - val_accuracy: 0.3445
Epoch 9317/10000
1/1 [==============================] - 0s 103ms/step - loss: 0.0041 - accuracy: 1.0000 - val_loss: 8.5855 - val_accuracy: 0.3444
Epoch 9318/10000
1/1 [==============================] - 0s 104ms/step - loss: 0.0041 - accuracy: 1.0000 - val_loss: 8.5863 - val_accuracy: 0.3445
Epoch 9319/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0041 - accuracy: 1.0000 - val_loss: 8.5871 - val_accuracy: 0.3443
Epoch 9320/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0041 - accuracy: 1.0000 - val_loss: 8.5878 - val_accuracy: 0.3445
Epoch 9321/10000
1/1 [==============================] - 0s 119ms/step - loss: 0.0041 - accuracy: 1.0000 - val_loss: 8.5885 - val_accuracy: 0.3445
Epoch 9322/10000
1/1 [==============================] - 0s 116ms/step - loss: 0.0041 - accuracy: 1.0000 - val_loss: 8.5894 - val_accuracy: 0.3445
Epoch 9323/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0041 - accuracy: 1.0000 - val_loss: 8.5901 - val_accuracy: 0.3445
Epoch 9324/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0041 - accuracy: 1.0000 - val_loss: 8.5907 - val_accuracy: 0.3445
Epoch 9325/10000
1/1 [==============================] - 0s 116ms/step - loss: 0.0041 - accuracy: 1.0000 - val_loss: 8.5914 - val_accuracy: 0.3444
Epoch 9326/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0041 - accuracy: 1.0000 - val_loss: 8.5921 - val_accuracy: 0.3444
Epoch 9327/10000
1/1 [==============================] - 0s 119ms/step - loss: 0.0041 - accuracy: 1.0000 - val_loss: 8.5928 - val_accuracy: 0.3445
Epoch 9328/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0041 - accuracy: 1.0000 - val_loss: 8.5935 - val_accuracy: 0.3445
Epoch 9329/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0041 - accuracy: 1.0000 - val_loss: 8.5942 - val_accuracy: 0.3445
Epoch 9330/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0041 - accuracy: 1.0000 - val_loss: 8.5948 - val_accuracy: 0.3444
Epoch 9331/10000
1/1 [==============================] - 0s 120ms/step - loss: 0.0041 - accuracy: 1.0000 - val_loss: 8.5952 - val_accuracy: 0.3444
Epoch 9332/10000
1/1 [==============================] - 0s 118ms/step - loss: 0.0041 - accuracy: 1.0000 - val_loss: 8.5957 - val_accuracy: 0.3444
Epoch 9333/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0041 - accuracy: 1.0000 - val_loss: 8.5963 - val_accuracy: 0.3444
Epoch 9334/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0041 - accuracy: 1.0000 - val_loss: 8.5971 - val_accuracy: 0.3444
Epoch 9335/10000
1/1 [==============================] - 0s 119ms/step - loss: 0.0040 - accuracy: 1.0000 - val_loss: 8.5979 - val_accuracy: 0.3444
Epoch 9336/10000
1/1 [==============================] - 0s 126ms/step - loss: 0.0040 - accuracy: 1.0000 - val_loss: 8.5988 - val_accuracy: 0.3443
Epoch 9337/10000
1/1 [==============================] - 0s 125ms/step - loss: 0.0040 - accuracy: 1.0000 - val_loss: 8.5995 - val_accuracy: 0.3443
Epoch 9338/10000
1/1 [==============================] - 0s 118ms/step - loss: 0.0040 - accuracy: 1.0000 - val_loss: 8.6000 - val_accuracy: 0.3444
Epoch 9339/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0040 - accuracy: 1.0000 - val_loss: 8.6004 - val_accuracy: 0.3444
Epoch 9340/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0040 - accuracy: 1.0000 - val_loss: 8.6010 - val_accuracy: 0.3444
Epoch 9341/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0040 - accuracy: 1.0000 - val_loss: 8.6017 - val_accuracy: 0.3443
Epoch 9342/10000
1/1 [==============================] - 0s 120ms/step - loss: 0.0040 - accuracy: 1.0000 - val_loss: 8.6024 - val_accuracy: 0.3444
Epoch 9343/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0040 - accuracy: 1.0000 - val_loss: 8.6032 - val_accuracy: 0.3444
Epoch 9344/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0040 - accuracy: 1.0000 - val_loss: 8.6041 - val_accuracy: 0.3443
Epoch 9345/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0040 - accuracy: 1.0000 - val_loss: 8.6050 - val_accuracy: 0.3443
Epoch 9346/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0040 - accuracy: 1.0000 - val_loss: 8.6056 - val_accuracy: 0.3444
Epoch 9347/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0040 - accuracy: 1.0000 - val_loss: 8.6062 - val_accuracy: 0.3444
Epoch 9348/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0040 - accuracy: 1.0000 - val_loss: 8.6069 - val_accuracy: 0.3445
Epoch 9349/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0040 - accuracy: 1.0000 - val_loss: 8.6076 - val_accuracy: 0.3444
Epoch 9350/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0040 - accuracy: 1.0000 - val_loss: 8.6083 - val_accuracy: 0.3444
Epoch 9351/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0040 - accuracy: 1.0000 - val_loss: 8.6091 - val_accuracy: 0.3444
Epoch 9352/10000
1/1 [==============================] - 0s 104ms/step - loss: 0.0040 - accuracy: 1.0000 - val_loss: 8.6099 - val_accuracy: 0.3444
Epoch 9353/10000
1/1 [==============================] - 0s 104ms/step - loss: 0.0040 - accuracy: 1.0000 - val_loss: 8.6106 - val_accuracy: 0.3444
Epoch 9354/10000
1/1 [==============================] - 0s 103ms/step - loss: 0.0040 - accuracy: 1.0000 - val_loss: 8.6113 - val_accuracy: 0.3444
Epoch 9355/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0040 - accuracy: 1.0000 - val_loss: 8.6118 - val_accuracy: 0.3443
Epoch 9356/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0040 - accuracy: 1.0000 - val_loss: 8.6124 - val_accuracy: 0.3443
Epoch 9357/10000
1/1 [==============================] - 0s 100ms/step - loss: 0.0040 - accuracy: 1.0000 - val_loss: 8.6130 - val_accuracy: 0.3444
Epoch 9358/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0040 - accuracy: 1.0000 - val_loss: 8.6137 - val_accuracy: 0.3444
Epoch 9359/10000
1/1 [==============================] - 0s 104ms/step - loss: 0.0040 - accuracy: 1.0000 - val_loss: 8.6145 - val_accuracy: 0.3444
Epoch 9360/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0040 - accuracy: 1.0000 - val_loss: 8.6151 - val_accuracy: 0.3444
Epoch 9361/10000
1/1 [==============================] - 0s 104ms/step - loss: 0.0040 - accuracy: 1.0000 - val_loss: 8.6156 - val_accuracy: 0.3444
Epoch 9362/10000
1/1 [==============================] - 0s 102ms/step - loss: 0.0040 - accuracy: 1.0000 - val_loss: 8.6162 - val_accuracy: 0.3443
Epoch 9363/10000
1/1 [==============================] - 0s 104ms/step - loss: 0.0040 - accuracy: 1.0000 - val_loss: 8.6168 - val_accuracy: 0.3444
Epoch 9364/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0040 - accuracy: 1.0000 - val_loss: 8.6176 - val_accuracy: 0.3443
Epoch 9365/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0040 - accuracy: 1.0000 - val_loss: 8.6184 - val_accuracy: 0.3444
Epoch 9366/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0039 - accuracy: 1.0000 - val_loss: 8.6192 - val_accuracy: 0.3444
Epoch 9367/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0039 - accuracy: 1.0000 - val_loss: 8.6200 - val_accuracy: 0.3444
Epoch 9368/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0039 - accuracy: 1.0000 - val_loss: 8.6205 - val_accuracy: 0.3442
Epoch 9369/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0039 - accuracy: 1.0000 - val_loss: 8.6213 - val_accuracy: 0.3441
Epoch 9370/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0039 - accuracy: 1.0000 - val_loss: 8.6219 - val_accuracy: 0.3442
Epoch 9371/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0039 - accuracy: 1.0000 - val_loss: 8.6227 - val_accuracy: 0.3443
Epoch 9372/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0039 - accuracy: 1.0000 - val_loss: 8.6233 - val_accuracy: 0.3442
Epoch 9373/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0039 - accuracy: 1.0000 - val_loss: 8.6240 - val_accuracy: 0.3442
Epoch 9374/10000
1/1 [==============================] - 0s 103ms/step - loss: 0.0039 - accuracy: 1.0000 - val_loss: 8.6246 - val_accuracy: 0.3443
Epoch 9375/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0039 - accuracy: 1.0000 - val_loss: 8.6254 - val_accuracy: 0.3444
Epoch 9376/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0039 - accuracy: 1.0000 - val_loss: 8.6261 - val_accuracy: 0.3443
Epoch 9377/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0039 - accuracy: 1.0000 - val_loss: 8.6268 - val_accuracy: 0.3443
Epoch 9378/10000
1/1 [==============================] - 0s 103ms/step - loss: 0.0039 - accuracy: 1.0000 - val_loss: 8.6275 - val_accuracy: 0.3441
Epoch 9379/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0039 - accuracy: 1.0000 - val_loss: 8.6282 - val_accuracy: 0.3443
Epoch 9380/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0039 - accuracy: 1.0000 - val_loss: 8.6289 - val_accuracy: 0.3444
Epoch 9381/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0039 - accuracy: 1.0000 - val_loss: 8.6295 - val_accuracy: 0.3443
Epoch 9382/10000
1/1 [==============================] - 0s 104ms/step - loss: 0.0039 - accuracy: 1.0000 - val_loss: 8.6302 - val_accuracy: 0.3444
Epoch 9383/10000
1/1 [==============================] - 0s 102ms/step - loss: 0.0039 - accuracy: 1.0000 - val_loss: 8.6308 - val_accuracy: 0.3443
Epoch 9384/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0039 - accuracy: 1.0000 - val_loss: 8.6315 - val_accuracy: 0.3442
Epoch 9385/10000
1/1 [==============================] - 0s 104ms/step - loss: 0.0039 - accuracy: 1.0000 - val_loss: 8.6320 - val_accuracy: 0.3442
Epoch 9386/10000
1/1 [==============================] - 0s 104ms/step - loss: 0.0039 - accuracy: 1.0000 - val_loss: 8.6325 - val_accuracy: 0.3444
Epoch 9387/10000
1/1 [==============================] - 0s 104ms/step - loss: 0.0039 - accuracy: 1.0000 - val_loss: 8.6331 - val_accuracy: 0.3443
Epoch 9388/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0039 - accuracy: 1.0000 - val_loss: 8.6338 - val_accuracy: 0.3442
Epoch 9389/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0039 - accuracy: 1.0000 - val_loss: 8.6346 - val_accuracy: 0.3442
Epoch 9390/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0039 - accuracy: 1.0000 - val_loss: 8.6353 - val_accuracy: 0.3443
Epoch 9391/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0039 - accuracy: 1.0000 - val_loss: 8.6361 - val_accuracy: 0.3441
Epoch 9392/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0039 - accuracy: 1.0000 - val_loss: 8.6367 - val_accuracy: 0.3443
Epoch 9393/10000
1/1 [==============================] - 0s 122ms/step - loss: 0.0039 - accuracy: 1.0000 - val_loss: 8.6372 - val_accuracy: 0.3443
Epoch 9394/10000
1/1 [==============================] - 0s 122ms/step - loss: 0.0039 - accuracy: 1.0000 - val_loss: 8.6377 - val_accuracy: 0.3443
Epoch 9395/10000
1/1 [==============================] - 0s 121ms/step - loss: 0.0039 - accuracy: 1.0000 - val_loss: 8.6385 - val_accuracy: 0.3443
Epoch 9396/10000
1/1 [==============================] - 0s 122ms/step - loss: 0.0039 - accuracy: 1.0000 - val_loss: 8.6393 - val_accuracy: 0.3443
Epoch 9397/10000
1/1 [==============================] - 0s 122ms/step - loss: 0.0039 - accuracy: 1.0000 - val_loss: 8.6402 - val_accuracy: 0.3442
Epoch 9398/10000
1/1 [==============================] - 0s 116ms/step - loss: 0.0038 - accuracy: 1.0000 - val_loss: 8.6411 - val_accuracy: 0.3443
Epoch 9399/10000
1/1 [==============================] - 0s 119ms/step - loss: 0.0038 - accuracy: 1.0000 - val_loss: 8.6418 - val_accuracy: 0.3443
Epoch 9400/10000
1/1 [==============================] - 0s 119ms/step - loss: 0.0038 - accuracy: 1.0000 - val_loss: 8.6422 - val_accuracy: 0.3443
Epoch 9401/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0038 - accuracy: 1.0000 - val_loss: 8.6427 - val_accuracy: 0.3445
Epoch 9402/10000
1/1 [==============================] - 0s 121ms/step - loss: 0.0038 - accuracy: 1.0000 - val_loss: 8.6433 - val_accuracy: 0.3444
Epoch 9403/10000
1/1 [==============================] - 0s 123ms/step - loss: 0.0038 - accuracy: 1.0000 - val_loss: 8.6441 - val_accuracy: 0.3445
Epoch 9404/10000
1/1 [==============================] - 0s 119ms/step - loss: 0.0038 - accuracy: 1.0000 - val_loss: 8.6450 - val_accuracy: 0.3443
Epoch 9405/10000
1/1 [==============================] - 0s 123ms/step - loss: 0.0038 - accuracy: 1.0000 - val_loss: 8.6458 - val_accuracy: 0.3442
Epoch 9406/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0038 - accuracy: 1.0000 - val_loss: 8.6464 - val_accuracy: 0.3442
Epoch 9407/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0038 - accuracy: 1.0000 - val_loss: 8.6469 - val_accuracy: 0.3442
Epoch 9408/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0038 - accuracy: 1.0000 - val_loss: 8.6474 - val_accuracy: 0.3442
Epoch 9409/10000
1/1 [==============================] - 0s 104ms/step - loss: 0.0038 - accuracy: 1.0000 - val_loss: 8.6480 - val_accuracy: 0.3443
Epoch 9410/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0038 - accuracy: 1.0000 - val_loss: 8.6487 - val_accuracy: 0.3443
Epoch 9411/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0038 - accuracy: 1.0000 - val_loss: 8.6495 - val_accuracy: 0.3442
Epoch 9412/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0038 - accuracy: 1.0000 - val_loss: 8.6504 - val_accuracy: 0.3443
Epoch 9413/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0038 - accuracy: 1.0000 - val_loss: 8.6512 - val_accuracy: 0.3444
Epoch 9414/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0038 - accuracy: 1.0000 - val_loss: 8.6521 - val_accuracy: 0.3444
Epoch 9415/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0038 - accuracy: 1.0000 - val_loss: 8.6528 - val_accuracy: 0.3442
Epoch 9416/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0038 - accuracy: 1.0000 - val_loss: 8.6533 - val_accuracy: 0.3443
Epoch 9417/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0038 - accuracy: 1.0000 - val_loss: 8.6538 - val_accuracy: 0.3444
Epoch 9418/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0038 - accuracy: 1.0000 - val_loss: 8.6544 - val_accuracy: 0.3443
Epoch 9419/10000
1/1 [==============================] - 0s 104ms/step - loss: 0.0038 - accuracy: 1.0000 - val_loss: 8.6550 - val_accuracy: 0.3443
Epoch 9420/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0038 - accuracy: 1.0000 - val_loss: 8.6558 - val_accuracy: 0.3444
Epoch 9421/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0038 - accuracy: 1.0000 - val_loss: 8.6567 - val_accuracy: 0.3442
Epoch 9422/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0038 - accuracy: 1.0000 - val_loss: 8.6572 - val_accuracy: 0.3444
Epoch 9423/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0038 - accuracy: 1.0000 - val_loss: 8.6579 - val_accuracy: 0.3443
Epoch 9424/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0038 - accuracy: 1.0000 - val_loss: 8.6584 - val_accuracy: 0.3443
Epoch 9425/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0038 - accuracy: 1.0000 - val_loss: 8.6590 - val_accuracy: 0.3442
Epoch 9426/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0038 - accuracy: 1.0000 - val_loss: 8.6597 - val_accuracy: 0.3443
Epoch 9427/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0038 - accuracy: 1.0000 - val_loss: 8.6605 - val_accuracy: 0.3442
Epoch 9428/10000
1/1 [==============================] - 0s 118ms/step - loss: 0.0038 - accuracy: 1.0000 - val_loss: 8.6612 - val_accuracy: 0.3443
Epoch 9429/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0038 - accuracy: 1.0000 - val_loss: 8.6619 - val_accuracy: 0.3443
Epoch 9430/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0038 - accuracy: 1.0000 - val_loss: 8.6625 - val_accuracy: 0.3444
Epoch 9431/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0037 - accuracy: 1.0000 - val_loss: 8.6632 - val_accuracy: 0.3443
Epoch 9432/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0037 - accuracy: 1.0000 - val_loss: 8.6638 - val_accuracy: 0.3444
Epoch 9433/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0037 - accuracy: 1.0000 - val_loss: 8.6646 - val_accuracy: 0.3444
Epoch 9434/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0037 - accuracy: 1.0000 - val_loss: 8.6653 - val_accuracy: 0.3444
Epoch 9435/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0037 - accuracy: 1.0000 - val_loss: 8.6660 - val_accuracy: 0.3444
Epoch 9436/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0037 - accuracy: 1.0000 - val_loss: 8.6666 - val_accuracy: 0.3443
Epoch 9437/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0037 - accuracy: 1.0000 - val_loss: 8.6672 - val_accuracy: 0.3443
Epoch 9438/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0037 - accuracy: 1.0000 - val_loss: 8.6679 - val_accuracy: 0.3443
Epoch 9439/10000
1/1 [==============================] - 0s 118ms/step - loss: 0.0037 - accuracy: 1.0000 - val_loss: 8.6687 - val_accuracy: 0.3443
Epoch 9440/10000
1/1 [==============================] - 0s 122ms/step - loss: 0.0037 - accuracy: 1.0000 - val_loss: 8.6694 - val_accuracy: 0.3444
Epoch 9441/10000
1/1 [==============================] - 0s 116ms/step - loss: 0.0037 - accuracy: 1.0000 - val_loss: 8.6701 - val_accuracy: 0.3443
Epoch 9442/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0037 - accuracy: 1.0000 - val_loss: 8.6707 - val_accuracy: 0.3444
Epoch 9443/10000
1/1 [==============================] - 0s 117ms/step - loss: 0.0037 - accuracy: 1.0000 - val_loss: 8.6713 - val_accuracy: 0.3443
Epoch 9444/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0037 - accuracy: 1.0000 - val_loss: 8.6719 - val_accuracy: 0.3443
Epoch 9445/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0037 - accuracy: 1.0000 - val_loss: 8.6726 - val_accuracy: 0.3443
Epoch 9446/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0037 - accuracy: 1.0000 - val_loss: 8.6732 - val_accuracy: 0.3443
Epoch 9447/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0037 - accuracy: 1.0000 - val_loss: 8.6739 - val_accuracy: 0.3443
Epoch 9448/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0037 - accuracy: 1.0000 - val_loss: 8.6746 - val_accuracy: 0.3444
Epoch 9449/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0037 - accuracy: 1.0000 - val_loss: 8.6752 - val_accuracy: 0.3444
Epoch 9450/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0037 - accuracy: 1.0000 - val_loss: 8.6760 - val_accuracy: 0.3443
Epoch 9451/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0037 - accuracy: 1.0000 - val_loss: 8.6768 - val_accuracy: 0.3444
Epoch 9452/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0037 - accuracy: 1.0000 - val_loss: 8.6776 - val_accuracy: 0.3443
Epoch 9453/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0037 - accuracy: 1.0000 - val_loss: 8.6780 - val_accuracy: 0.3443
Epoch 9454/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0037 - accuracy: 1.0000 - val_loss: 8.6786 - val_accuracy: 0.3442
Epoch 9455/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0037 - accuracy: 1.0000 - val_loss: 8.6793 - val_accuracy: 0.3443
Epoch 9456/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0037 - accuracy: 1.0000 - val_loss: 8.6801 - val_accuracy: 0.3441
Epoch 9457/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0037 - accuracy: 1.0000 - val_loss: 8.6809 - val_accuracy: 0.3441
Epoch 9458/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0037 - accuracy: 1.0000 - val_loss: 8.6816 - val_accuracy: 0.3442
Epoch 9459/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0037 - accuracy: 1.0000 - val_loss: 8.6822 - val_accuracy: 0.3443
Epoch 9460/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0037 - accuracy: 1.0000 - val_loss: 8.6828 - val_accuracy: 0.3443
Epoch 9461/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0037 - accuracy: 1.0000 - val_loss: 8.6835 - val_accuracy: 0.3443
Epoch 9462/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0037 - accuracy: 1.0000 - val_loss: 8.6841 - val_accuracy: 0.3443
Epoch 9463/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0037 - accuracy: 1.0000 - val_loss: 8.6849 - val_accuracy: 0.3444
Epoch 9464/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0037 - accuracy: 1.0000 - val_loss: 8.6857 - val_accuracy: 0.3443
Epoch 9465/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0036 - accuracy: 1.0000 - val_loss: 8.6864 - val_accuracy: 0.3443
Epoch 9466/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0036 - accuracy: 1.0000 - val_loss: 8.6869 - val_accuracy: 0.3441
Epoch 9467/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0036 - accuracy: 1.0000 - val_loss: 8.6874 - val_accuracy: 0.3442
Epoch 9468/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0036 - accuracy: 1.0000 - val_loss: 8.6878 - val_accuracy: 0.3443
Epoch 9469/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0036 - accuracy: 1.0000 - val_loss: 8.6883 - val_accuracy: 0.3442
Epoch 9470/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0036 - accuracy: 1.0000 - val_loss: 8.6891 - val_accuracy: 0.3443
Epoch 9471/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0036 - accuracy: 1.0000 - val_loss: 8.6899 - val_accuracy: 0.3442
Epoch 9472/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0036 - accuracy: 1.0000 - val_loss: 8.6909 - val_accuracy: 0.3441
Epoch 9473/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0036 - accuracy: 1.0000 - val_loss: 8.6916 - val_accuracy: 0.3442
Epoch 9474/10000
1/1 [==============================] - 0s 118ms/step - loss: 0.0036 - accuracy: 1.0000 - val_loss: 8.6923 - val_accuracy: 0.3442
Epoch 9475/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0036 - accuracy: 1.0000 - val_loss: 8.6929 - val_accuracy: 0.3440
Epoch 9476/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0036 - accuracy: 1.0000 - val_loss: 8.6934 - val_accuracy: 0.3440
Epoch 9477/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0036 - accuracy: 1.0000 - val_loss: 8.6940 - val_accuracy: 0.3442
Epoch 9478/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0036 - accuracy: 1.0000 - val_loss: 8.6947 - val_accuracy: 0.3440
Epoch 9479/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0036 - accuracy: 1.0000 - val_loss: 8.6954 - val_accuracy: 0.3442
Epoch 9480/10000
1/1 [==============================] - 0s 119ms/step - loss: 0.0036 - accuracy: 1.0000 - val_loss: 8.6963 - val_accuracy: 0.3443
Epoch 9481/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0036 - accuracy: 1.0000 - val_loss: 8.6971 - val_accuracy: 0.3442
Epoch 9482/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0036 - accuracy: 1.0000 - val_loss: 8.6978 - val_accuracy: 0.3440
Epoch 9483/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0036 - accuracy: 1.0000 - val_loss: 8.6983 - val_accuracy: 0.3440
Epoch 9484/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0036 - accuracy: 1.0000 - val_loss: 8.6990 - val_accuracy: 0.3441
Epoch 9485/10000
1/1 [==============================] - 0s 116ms/step - loss: 0.0036 - accuracy: 1.0000 - val_loss: 8.6997 - val_accuracy: 0.3440
Epoch 9486/10000
1/1 [==============================] - 0s 119ms/step - loss: 0.0036 - accuracy: 1.0000 - val_loss: 8.7004 - val_accuracy: 0.3442
Epoch 9487/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0036 - accuracy: 1.0000 - val_loss: 8.7012 - val_accuracy: 0.3442
Epoch 9488/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0036 - accuracy: 1.0000 - val_loss: 8.7018 - val_accuracy: 0.3441
Epoch 9489/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0036 - accuracy: 1.0000 - val_loss: 8.7024 - val_accuracy: 0.3441
Epoch 9490/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0036 - accuracy: 1.0000 - val_loss: 8.7031 - val_accuracy: 0.3441
Epoch 9491/10000
1/1 [==============================] - 0s 118ms/step - loss: 0.0036 - accuracy: 1.0000 - val_loss: 8.7035 - val_accuracy: 0.3439
Epoch 9492/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0036 - accuracy: 1.0000 - val_loss: 8.7039 - val_accuracy: 0.3442
Epoch 9493/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0036 - accuracy: 1.0000 - val_loss: 8.7044 - val_accuracy: 0.3441
Epoch 9494/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0036 - accuracy: 1.0000 - val_loss: 8.7051 - val_accuracy: 0.3442
Epoch 9495/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0036 - accuracy: 1.0000 - val_loss: 8.7059 - val_accuracy: 0.3443
Epoch 9496/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0036 - accuracy: 1.0000 - val_loss: 8.7069 - val_accuracy: 0.3440
Epoch 9497/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0036 - accuracy: 1.0000 - val_loss: 8.7077 - val_accuracy: 0.3440
Epoch 9498/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0036 - accuracy: 1.0000 - val_loss: 8.7084 - val_accuracy: 0.3439
Epoch 9499/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0036 - accuracy: 1.0000 - val_loss: 8.7090 - val_accuracy: 0.3442
Epoch 9500/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0035 - accuracy: 1.0000 - val_loss: 8.7095 - val_accuracy: 0.3443
Epoch 9501/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0035 - accuracy: 1.0000 - val_loss: 8.7100 - val_accuracy: 0.3442
Epoch 9502/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0035 - accuracy: 1.0000 - val_loss: 8.7105 - val_accuracy: 0.3442
Epoch 9503/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0035 - accuracy: 1.0000 - val_loss: 8.7112 - val_accuracy: 0.3441
Epoch 9504/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0035 - accuracy: 1.0000 - val_loss: 8.7120 - val_accuracy: 0.3442
Epoch 9505/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0035 - accuracy: 1.0000 - val_loss: 8.7128 - val_accuracy: 0.3444
Epoch 9506/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0035 - accuracy: 1.0000 - val_loss: 8.7135 - val_accuracy: 0.3444
Epoch 9507/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0035 - accuracy: 1.0000 - val_loss: 8.7141 - val_accuracy: 0.3442
Epoch 9508/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0035 - accuracy: 1.0000 - val_loss: 8.7146 - val_accuracy: 0.3442
Epoch 9509/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0035 - accuracy: 1.0000 - val_loss: 8.7152 - val_accuracy: 0.3443
Epoch 9510/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0035 - accuracy: 1.0000 - val_loss: 8.7159 - val_accuracy: 0.3443
Epoch 9511/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0035 - accuracy: 1.0000 - val_loss: 8.7169 - val_accuracy: 0.3443
Epoch 9512/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0035 - accuracy: 1.0000 - val_loss: 8.7176 - val_accuracy: 0.3439
Epoch 9513/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0035 - accuracy: 1.0000 - val_loss: 8.7186 - val_accuracy: 0.3440
Epoch 9514/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0035 - accuracy: 1.0000 - val_loss: 8.7193 - val_accuracy: 0.3440
Epoch 9515/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0035 - accuracy: 1.0000 - val_loss: 8.7197 - val_accuracy: 0.3440
Epoch 9516/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0035 - accuracy: 1.0000 - val_loss: 8.7202 - val_accuracy: 0.3442
Epoch 9517/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0035 - accuracy: 1.0000 - val_loss: 8.7206 - val_accuracy: 0.3443
Epoch 9518/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0035 - accuracy: 1.0000 - val_loss: 8.7212 - val_accuracy: 0.3443
Epoch 9519/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0035 - accuracy: 1.0000 - val_loss: 8.7220 - val_accuracy: 0.3442
Epoch 9520/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0035 - accuracy: 1.0000 - val_loss: 8.7228 - val_accuracy: 0.3443
Epoch 9521/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0035 - accuracy: 1.0000 - val_loss: 8.7235 - val_accuracy: 0.3441
Epoch 9522/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0035 - accuracy: 1.0000 - val_loss: 8.7243 - val_accuracy: 0.3443
Epoch 9523/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0035 - accuracy: 1.0000 - val_loss: 8.7250 - val_accuracy: 0.3443
Epoch 9524/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0035 - accuracy: 1.0000 - val_loss: 8.7255 - val_accuracy: 0.3443
Epoch 9525/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0035 - accuracy: 1.0000 - val_loss: 8.7260 - val_accuracy: 0.3442
Epoch 9526/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0035 - accuracy: 1.0000 - val_loss: 8.7266 - val_accuracy: 0.3444
Epoch 9527/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0035 - accuracy: 1.0000 - val_loss: 8.7273 - val_accuracy: 0.3442
Epoch 9528/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0035 - accuracy: 1.0000 - val_loss: 8.7281 - val_accuracy: 0.3440
Epoch 9529/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0035 - accuracy: 1.0000 - val_loss: 8.7290 - val_accuracy: 0.3443
Epoch 9530/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0035 - accuracy: 1.0000 - val_loss: 8.7298 - val_accuracy: 0.3442
Epoch 9531/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0035 - accuracy: 1.0000 - val_loss: 8.7305 - val_accuracy: 0.3442
Epoch 9532/10000
1/1 [==============================] - 0s 120ms/step - loss: 0.0035 - accuracy: 1.0000 - val_loss: 8.7309 - val_accuracy: 0.3443
Epoch 9533/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0035 - accuracy: 1.0000 - val_loss: 8.7313 - val_accuracy: 0.3443
Epoch 9534/10000
1/1 [==============================] - 0s 121ms/step - loss: 0.0035 - accuracy: 1.0000 - val_loss: 8.7319 - val_accuracy: 0.3443
Epoch 9535/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0035 - accuracy: 1.0000 - val_loss: 8.7325 - val_accuracy: 0.3444
Epoch 9536/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0034 - accuracy: 1.0000 - val_loss: 8.7333 - val_accuracy: 0.3443
Epoch 9537/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0034 - accuracy: 1.0000 - val_loss: 8.7341 - val_accuracy: 0.3444
Epoch 9538/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0034 - accuracy: 1.0000 - val_loss: 8.7348 - val_accuracy: 0.3441
Epoch 9539/10000
1/1 [==============================] - 0s 119ms/step - loss: 0.0034 - accuracy: 1.0000 - val_loss: 8.7354 - val_accuracy: 0.3442
Epoch 9540/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0034 - accuracy: 1.0000 - val_loss: 8.7360 - val_accuracy: 0.3443
Epoch 9541/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0034 - accuracy: 1.0000 - val_loss: 8.7365 - val_accuracy: 0.3442
Epoch 9542/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0034 - accuracy: 1.0000 - val_loss: 8.7371 - val_accuracy: 0.3443
Epoch 9543/10000
1/1 [==============================] - 0s 121ms/step - loss: 0.0034 - accuracy: 1.0000 - val_loss: 8.7379 - val_accuracy: 0.3443
Epoch 9544/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0034 - accuracy: 1.0000 - val_loss: 8.7387 - val_accuracy: 0.3441
Epoch 9545/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0034 - accuracy: 1.0000 - val_loss: 8.7394 - val_accuracy: 0.3441
Epoch 9546/10000
1/1 [==============================] - 0s 117ms/step - loss: 0.0034 - accuracy: 1.0000 - val_loss: 8.7400 - val_accuracy: 0.3443
Epoch 9547/10000
1/1 [==============================] - 0s 120ms/step - loss: 0.0034 - accuracy: 1.0000 - val_loss: 8.7406 - val_accuracy: 0.3441
Epoch 9548/10000
1/1 [==============================] - 0s 119ms/step - loss: 0.0034 - accuracy: 1.0000 - val_loss: 8.7411 - val_accuracy: 0.3443
Epoch 9549/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0034 - accuracy: 1.0000 - val_loss: 8.7417 - val_accuracy: 0.3443
Epoch 9550/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0034 - accuracy: 1.0000 - val_loss: 8.7425 - val_accuracy: 0.3443
Epoch 9551/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0034 - accuracy: 1.0000 - val_loss: 8.7433 - val_accuracy: 0.3442
Epoch 9552/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0034 - accuracy: 1.0000 - val_loss: 8.7440 - val_accuracy: 0.3444
Epoch 9553/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0034 - accuracy: 1.0000 - val_loss: 8.7447 - val_accuracy: 0.3440
Epoch 9554/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0034 - accuracy: 1.0000 - val_loss: 8.7454 - val_accuracy: 0.3443
Epoch 9555/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0034 - accuracy: 1.0000 - val_loss: 8.7459 - val_accuracy: 0.3443
Epoch 9556/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0034 - accuracy: 1.0000 - val_loss: 8.7465 - val_accuracy: 0.3442
Epoch 9557/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0034 - accuracy: 1.0000 - val_loss: 8.7472 - val_accuracy: 0.3445
Epoch 9558/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0034 - accuracy: 1.0000 - val_loss: 8.7478 - val_accuracy: 0.3443
Epoch 9559/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0034 - accuracy: 1.0000 - val_loss: 8.7485 - val_accuracy: 0.3444
Epoch 9560/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0034 - accuracy: 1.0000 - val_loss: 8.7491 - val_accuracy: 0.3444
Epoch 9561/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0034 - accuracy: 1.0000 - val_loss: 8.7497 - val_accuracy: 0.3444
Epoch 9562/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0034 - accuracy: 1.0000 - val_loss: 8.7505 - val_accuracy: 0.3443
Epoch 9563/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0034 - accuracy: 1.0000 - val_loss: 8.7512 - val_accuracy: 0.3444
Epoch 9564/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0034 - accuracy: 1.0000 - val_loss: 8.7520 - val_accuracy: 0.3441
Epoch 9565/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0034 - accuracy: 1.0000 - val_loss: 8.7526 - val_accuracy: 0.3443
Epoch 9566/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0034 - accuracy: 1.0000 - val_loss: 8.7531 - val_accuracy: 0.3444
Epoch 9567/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0034 - accuracy: 1.0000 - val_loss: 8.7536 - val_accuracy: 0.3445
Epoch 9568/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0034 - accuracy: 1.0000 - val_loss: 8.7541 - val_accuracy: 0.3445
Epoch 9569/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0034 - accuracy: 1.0000 - val_loss: 8.7548 - val_accuracy: 0.3445
Epoch 9570/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0034 - accuracy: 1.0000 - val_loss: 8.7554 - val_accuracy: 0.3445
Epoch 9571/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0034 - accuracy: 1.0000 - val_loss: 8.7562 - val_accuracy: 0.3443
Epoch 9572/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0034 - accuracy: 1.0000 - val_loss: 8.7569 - val_accuracy: 0.3442
Epoch 9573/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0034 - accuracy: 1.0000 - val_loss: 8.7574 - val_accuracy: 0.3444
Epoch 9574/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0033 - accuracy: 1.0000 - val_loss: 8.7582 - val_accuracy: 0.3445
Epoch 9575/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0033 - accuracy: 1.0000 - val_loss: 8.7590 - val_accuracy: 0.3444
Epoch 9576/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0033 - accuracy: 1.0000 - val_loss: 8.7598 - val_accuracy: 0.3444
Epoch 9577/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0033 - accuracy: 1.0000 - val_loss: 8.7607 - val_accuracy: 0.3443
Epoch 9578/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0033 - accuracy: 1.0000 - val_loss: 8.7615 - val_accuracy: 0.3443
Epoch 9579/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0033 - accuracy: 1.0000 - val_loss: 8.7620 - val_accuracy: 0.3444
Epoch 9580/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0033 - accuracy: 1.0000 - val_loss: 8.7625 - val_accuracy: 0.3444
Epoch 9581/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0033 - accuracy: 1.0000 - val_loss: 8.7631 - val_accuracy: 0.3446
Epoch 9582/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0033 - accuracy: 1.0000 - val_loss: 8.7637 - val_accuracy: 0.3447
Epoch 9583/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0033 - accuracy: 1.0000 - val_loss: 8.7643 - val_accuracy: 0.3445
Epoch 9584/10000
1/1 [==============================] - 0s 104ms/step - loss: 0.0033 - accuracy: 1.0000 - val_loss: 8.7651 - val_accuracy: 0.3444
Epoch 9585/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0033 - accuracy: 1.0000 - val_loss: 8.7657 - val_accuracy: 0.3445
Epoch 9586/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0033 - accuracy: 1.0000 - val_loss: 8.7663 - val_accuracy: 0.3445
Epoch 9587/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0033 - accuracy: 1.0000 - val_loss: 8.7670 - val_accuracy: 0.3443
Epoch 9588/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0033 - accuracy: 1.0000 - val_loss: 8.7677 - val_accuracy: 0.3443
Epoch 9589/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0033 - accuracy: 1.0000 - val_loss: 8.7685 - val_accuracy: 0.3444
Epoch 9590/10000
1/1 [==============================] - 0s 104ms/step - loss: 0.0033 - accuracy: 1.0000 - val_loss: 8.7693 - val_accuracy: 0.3444
Epoch 9591/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0033 - accuracy: 1.0000 - val_loss: 8.7698 - val_accuracy: 0.3444
Epoch 9592/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0033 - accuracy: 1.0000 - val_loss: 8.7704 - val_accuracy: 0.3443
Epoch 9593/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0033 - accuracy: 1.0000 - val_loss: 8.7710 - val_accuracy: 0.3443
Epoch 9594/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0033 - accuracy: 1.0000 - val_loss: 8.7717 - val_accuracy: 0.3442
Epoch 9595/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0033 - accuracy: 1.0000 - val_loss: 8.7724 - val_accuracy: 0.3444
Epoch 9596/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0033 - accuracy: 1.0000 - val_loss: 8.7731 - val_accuracy: 0.3445
Epoch 9597/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0033 - accuracy: 1.0000 - val_loss: 8.7736 - val_accuracy: 0.3443
Epoch 9598/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0033 - accuracy: 1.0000 - val_loss: 8.7743 - val_accuracy: 0.3444
Epoch 9599/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0033 - accuracy: 1.0000 - val_loss: 8.7750 - val_accuracy: 0.3444
Epoch 9600/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0033 - accuracy: 1.0000 - val_loss: 8.7759 - val_accuracy: 0.3445
Epoch 9601/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0033 - accuracy: 1.0000 - val_loss: 8.7765 - val_accuracy: 0.3444
Epoch 9602/10000
1/1 [==============================] - 0s 104ms/step - loss: 0.0033 - accuracy: 1.0000 - val_loss: 8.7770 - val_accuracy: 0.3443
Epoch 9603/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0033 - accuracy: 1.0000 - val_loss: 8.7776 - val_accuracy: 0.3445
Epoch 9604/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0033 - accuracy: 1.0000 - val_loss: 8.7782 - val_accuracy: 0.3442
Epoch 9605/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0033 - accuracy: 1.0000 - val_loss: 8.7789 - val_accuracy: 0.3443
Epoch 9606/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0033 - accuracy: 1.0000 - val_loss: 8.7796 - val_accuracy: 0.3442
Epoch 9607/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0033 - accuracy: 1.0000 - val_loss: 8.7802 - val_accuracy: 0.3444
Epoch 9608/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0033 - accuracy: 1.0000 - val_loss: 8.7809 - val_accuracy: 0.3446
Epoch 9609/10000
1/1 [==============================] - 0s 116ms/step - loss: 0.0033 - accuracy: 1.0000 - val_loss: 8.7814 - val_accuracy: 0.3445
Epoch 9610/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0033 - accuracy: 1.0000 - val_loss: 8.7819 - val_accuracy: 0.3445
Epoch 9611/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0033 - accuracy: 1.0000 - val_loss: 8.7825 - val_accuracy: 0.3445
Epoch 9612/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0033 - accuracy: 1.0000 - val_loss: 8.7830 - val_accuracy: 0.3444
Epoch 9613/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0032 - accuracy: 1.0000 - val_loss: 8.7837 - val_accuracy: 0.3446
Epoch 9614/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0032 - accuracy: 1.0000 - val_loss: 8.7845 - val_accuracy: 0.3445
Epoch 9615/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0032 - accuracy: 1.0000 - val_loss: 8.7854 - val_accuracy: 0.3445
Epoch 9616/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0032 - accuracy: 1.0000 - val_loss: 8.7861 - val_accuracy: 0.3446
Epoch 9617/10000
1/1 [==============================] - 0s 104ms/step - loss: 0.0032 - accuracy: 1.0000 - val_loss: 8.7867 - val_accuracy: 0.3446
Epoch 9618/10000
1/1 [==============================] - 0s 104ms/step - loss: 0.0032 - accuracy: 1.0000 - val_loss: 8.7873 - val_accuracy: 0.3444
Epoch 9619/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0032 - accuracy: 1.0000 - val_loss: 8.7880 - val_accuracy: 0.3445
Epoch 9620/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0032 - accuracy: 1.0000 - val_loss: 8.7887 - val_accuracy: 0.3445
Epoch 9621/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0032 - accuracy: 1.0000 - val_loss: 8.7896 - val_accuracy: 0.3448
Epoch 9622/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0032 - accuracy: 1.0000 - val_loss: 8.7903 - val_accuracy: 0.3447
Epoch 9623/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0032 - accuracy: 1.0000 - val_loss: 8.7909 - val_accuracy: 0.3447
Epoch 9624/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0032 - accuracy: 1.0000 - val_loss: 8.7913 - val_accuracy: 0.3445
Epoch 9625/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0032 - accuracy: 1.0000 - val_loss: 8.7920 - val_accuracy: 0.3445
Epoch 9626/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0032 - accuracy: 1.0000 - val_loss: 8.7925 - val_accuracy: 0.3444
Epoch 9627/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0032 - accuracy: 1.0000 - val_loss: 8.7932 - val_accuracy: 0.3446
Epoch 9628/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0032 - accuracy: 1.0000 - val_loss: 8.7941 - val_accuracy: 0.3446
Epoch 9629/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0032 - accuracy: 1.0000 - val_loss: 8.7949 - val_accuracy: 0.3445
Epoch 9630/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0032 - accuracy: 1.0000 - val_loss: 8.7956 - val_accuracy: 0.3445
Epoch 9631/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0032 - accuracy: 1.0000 - val_loss: 8.7963 - val_accuracy: 0.3444
Epoch 9632/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0032 - accuracy: 1.0000 - val_loss: 8.7969 - val_accuracy: 0.3444
Epoch 9633/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0032 - accuracy: 1.0000 - val_loss: 8.7974 - val_accuracy: 0.3447
Epoch 9634/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0032 - accuracy: 1.0000 - val_loss: 8.7979 - val_accuracy: 0.3445
Epoch 9635/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0032 - accuracy: 1.0000 - val_loss: 8.7985 - val_accuracy: 0.3446
Epoch 9636/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0032 - accuracy: 1.0000 - val_loss: 8.7992 - val_accuracy: 0.3448
Epoch 9637/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0032 - accuracy: 1.0000 - val_loss: 8.7999 - val_accuracy: 0.3446
Epoch 9638/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0032 - accuracy: 1.0000 - val_loss: 8.8007 - val_accuracy: 0.3446
Epoch 9639/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0032 - accuracy: 1.0000 - val_loss: 8.8015 - val_accuracy: 0.3445
Epoch 9640/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0032 - accuracy: 1.0000 - val_loss: 8.8021 - val_accuracy: 0.3446
Epoch 9641/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0032 - accuracy: 1.0000 - val_loss: 8.8028 - val_accuracy: 0.3445
Epoch 9642/10000
1/1 [==============================] - 0s 117ms/step - loss: 0.0032 - accuracy: 1.0000 - val_loss: 8.8035 - val_accuracy: 0.3445
Epoch 9643/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0032 - accuracy: 1.0000 - val_loss: 8.8040 - val_accuracy: 0.3445
Epoch 9644/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0032 - accuracy: 1.0000 - val_loss: 8.8046 - val_accuracy: 0.3444
Epoch 9645/10000
1/1 [==============================] - 0s 104ms/step - loss: 0.0032 - accuracy: 1.0000 - val_loss: 8.8053 - val_accuracy: 0.3445
Epoch 9646/10000
1/1 [==============================] - 0s 117ms/step - loss: 0.0032 - accuracy: 1.0000 - val_loss: 8.8059 - val_accuracy: 0.3445
Epoch 9647/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0032 - accuracy: 1.0000 - val_loss: 8.8065 - val_accuracy: 0.3445
Epoch 9648/10000
1/1 [==============================] - 0s 117ms/step - loss: 0.0032 - accuracy: 1.0000 - val_loss: 8.8071 - val_accuracy: 0.3446
Epoch 9649/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0032 - accuracy: 1.0000 - val_loss: 8.8076 - val_accuracy: 0.3446
Epoch 9650/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0032 - accuracy: 1.0000 - val_loss: 8.8082 - val_accuracy: 0.3445
Epoch 9651/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0032 - accuracy: 1.0000 - val_loss: 8.8090 - val_accuracy: 0.3445
Epoch 9652/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0032 - accuracy: 1.0000 - val_loss: 8.8098 - val_accuracy: 0.3444
Epoch 9653/10000
1/1 [==============================] - 0s 120ms/step - loss: 0.0031 - accuracy: 1.0000 - val_loss: 8.8107 - val_accuracy: 0.3445
Epoch 9654/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0031 - accuracy: 1.0000 - val_loss: 8.8114 - val_accuracy: 0.3445
Epoch 9655/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0031 - accuracy: 1.0000 - val_loss: 8.8119 - val_accuracy: 0.3444
Epoch 9656/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0031 - accuracy: 1.0000 - val_loss: 8.8124 - val_accuracy: 0.3444
Epoch 9657/10000
1/1 [==============================] - 0s 119ms/step - loss: 0.0031 - accuracy: 1.0000 - val_loss: 8.8130 - val_accuracy: 0.3443
Epoch 9658/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0031 - accuracy: 1.0000 - val_loss: 8.8137 - val_accuracy: 0.3446
Epoch 9659/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0031 - accuracy: 1.0000 - val_loss: 8.8142 - val_accuracy: 0.3445
Epoch 9660/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0031 - accuracy: 1.0000 - val_loss: 8.8148 - val_accuracy: 0.3443
Epoch 9661/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0031 - accuracy: 1.0000 - val_loss: 8.8155 - val_accuracy: 0.3446
Epoch 9662/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0031 - accuracy: 1.0000 - val_loss: 8.8162 - val_accuracy: 0.3446
Epoch 9663/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0031 - accuracy: 1.0000 - val_loss: 8.8171 - val_accuracy: 0.3445
Epoch 9664/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0031 - accuracy: 1.0000 - val_loss: 8.8178 - val_accuracy: 0.3445
Epoch 9665/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0031 - accuracy: 1.0000 - val_loss: 8.8185 - val_accuracy: 0.3445
Epoch 9666/10000
1/1 [==============================] - 0s 103ms/step - loss: 0.0031 - accuracy: 1.0000 - val_loss: 8.8192 - val_accuracy: 0.3442
Epoch 9667/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0031 - accuracy: 1.0000 - val_loss: 8.8196 - val_accuracy: 0.3446
Epoch 9668/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0031 - accuracy: 1.0000 - val_loss: 8.8201 - val_accuracy: 0.3446
Epoch 9669/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0031 - accuracy: 1.0000 - val_loss: 8.8206 - val_accuracy: 0.3448
Epoch 9670/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0031 - accuracy: 1.0000 - val_loss: 8.8212 - val_accuracy: 0.3447
Epoch 9671/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0031 - accuracy: 1.0000 - val_loss: 8.8219 - val_accuracy: 0.3446
Epoch 9672/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0031 - accuracy: 1.0000 - val_loss: 8.8227 - val_accuracy: 0.3446
Epoch 9673/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0031 - accuracy: 1.0000 - val_loss: 8.8236 - val_accuracy: 0.3447
Epoch 9674/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0031 - accuracy: 1.0000 - val_loss: 8.8244 - val_accuracy: 0.3445
Epoch 9675/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0031 - accuracy: 1.0000 - val_loss: 8.8249 - val_accuracy: 0.3446
Epoch 9676/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0031 - accuracy: 1.0000 - val_loss: 8.8253 - val_accuracy: 0.3446
Epoch 9677/10000
1/1 [==============================] - 0s 104ms/step - loss: 0.0031 - accuracy: 1.0000 - val_loss: 8.8258 - val_accuracy: 0.3447
Epoch 9678/10000
1/1 [==============================] - 0s 102ms/step - loss: 0.0031 - accuracy: 1.0000 - val_loss: 8.8265 - val_accuracy: 0.3445
Epoch 9679/10000
1/1 [==============================] - 0s 117ms/step - loss: 0.0031 - accuracy: 1.0000 - val_loss: 8.8272 - val_accuracy: 0.3446
Epoch 9680/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0031 - accuracy: 1.0000 - val_loss: 8.8281 - val_accuracy: 0.3444
Epoch 9681/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0031 - accuracy: 1.0000 - val_loss: 8.8289 - val_accuracy: 0.3445
Epoch 9682/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0031 - accuracy: 1.0000 - val_loss: 8.8294 - val_accuracy: 0.3446
Epoch 9683/10000
1/1 [==============================] - 0s 103ms/step - loss: 0.0031 - accuracy: 1.0000 - val_loss: 8.8301 - val_accuracy: 0.3444
Epoch 9684/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0031 - accuracy: 1.0000 - val_loss: 8.8305 - val_accuracy: 0.3445
Epoch 9685/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0031 - accuracy: 1.0000 - val_loss: 8.8311 - val_accuracy: 0.3447
Epoch 9686/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0031 - accuracy: 1.0000 - val_loss: 8.8316 - val_accuracy: 0.3446
Epoch 9687/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0031 - accuracy: 1.0000 - val_loss: 8.8324 - val_accuracy: 0.3445
Epoch 9688/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0031 - accuracy: 1.0000 - val_loss: 8.8330 - val_accuracy: 0.3446
Epoch 9689/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0031 - accuracy: 1.0000 - val_loss: 8.8339 - val_accuracy: 0.3447
Epoch 9690/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0031 - accuracy: 1.0000 - val_loss: 8.8347 - val_accuracy: 0.3446
Epoch 9691/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0031 - accuracy: 1.0000 - val_loss: 8.8355 - val_accuracy: 0.3446
Epoch 9692/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0031 - accuracy: 1.0000 - val_loss: 8.8359 - val_accuracy: 0.3446
Epoch 9693/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0031 - accuracy: 1.0000 - val_loss: 8.8366 - val_accuracy: 0.3444
Epoch 9694/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0031 - accuracy: 1.0000 - val_loss: 8.8372 - val_accuracy: 0.3446
Epoch 9695/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0030 - accuracy: 1.0000 - val_loss: 8.8379 - val_accuracy: 0.3444
Epoch 9696/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0030 - accuracy: 1.0000 - val_loss: 8.8388 - val_accuracy: 0.3445
Epoch 9697/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0030 - accuracy: 1.0000 - val_loss: 8.8392 - val_accuracy: 0.3449
Epoch 9698/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0030 - accuracy: 1.0000 - val_loss: 8.8398 - val_accuracy: 0.3446
Epoch 9699/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0030 - accuracy: 1.0000 - val_loss: 8.8404 - val_accuracy: 0.3448
Epoch 9700/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0030 - accuracy: 1.0000 - val_loss: 8.8410 - val_accuracy: 0.3449
Epoch 9701/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0030 - accuracy: 1.0000 - val_loss: 8.8417 - val_accuracy: 0.3450
Epoch 9702/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0030 - accuracy: 1.0000 - val_loss: 8.8425 - val_accuracy: 0.3450
Epoch 9703/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0030 - accuracy: 1.0000 - val_loss: 8.8432 - val_accuracy: 0.3448
Epoch 9704/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0030 - accuracy: 1.0000 - val_loss: 8.8440 - val_accuracy: 0.3448
Epoch 9705/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0030 - accuracy: 1.0000 - val_loss: 8.8446 - val_accuracy: 0.3448
Epoch 9706/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0030 - accuracy: 1.0000 - val_loss: 8.8451 - val_accuracy: 0.3448
Epoch 9707/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0030 - accuracy: 1.0000 - val_loss: 8.8456 - val_accuracy: 0.3449
Epoch 9708/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0030 - accuracy: 1.0000 - val_loss: 8.8463 - val_accuracy: 0.3449
Epoch 9709/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0030 - accuracy: 1.0000 - val_loss: 8.8470 - val_accuracy: 0.3448
Epoch 9710/10000
1/1 [==============================] - 0s 103ms/step - loss: 0.0030 - accuracy: 1.0000 - val_loss: 8.8477 - val_accuracy: 0.3447
Epoch 9711/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0030 - accuracy: 1.0000 - val_loss: 8.8485 - val_accuracy: 0.3447
Epoch 9712/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0030 - accuracy: 1.0000 - val_loss: 8.8491 - val_accuracy: 0.3449
Epoch 9713/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0030 - accuracy: 1.0000 - val_loss: 8.8496 - val_accuracy: 0.3448
Epoch 9714/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0030 - accuracy: 1.0000 - val_loss: 8.8501 - val_accuracy: 0.3447
Epoch 9715/10000
1/1 [==============================] - 0s 104ms/step - loss: 0.0030 - accuracy: 1.0000 - val_loss: 8.8508 - val_accuracy: 0.3449
Epoch 9716/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0030 - accuracy: 1.0000 - val_loss: 8.8514 - val_accuracy: 0.3447
Epoch 9717/10000
1/1 [==============================] - 0s 101ms/step - loss: 0.0030 - accuracy: 1.0000 - val_loss: 8.8523 - val_accuracy: 0.3447
Epoch 9718/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0030 - accuracy: 1.0000 - val_loss: 8.8531 - val_accuracy: 0.3447
Epoch 9719/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0030 - accuracy: 1.0000 - val_loss: 8.8538 - val_accuracy: 0.3447
Epoch 9720/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0030 - accuracy: 1.0000 - val_loss: 8.8544 - val_accuracy: 0.3447
Epoch 9721/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0030 - accuracy: 1.0000 - val_loss: 8.8549 - val_accuracy: 0.3447
Epoch 9722/10000
1/1 [==============================] - 0s 102ms/step - loss: 0.0030 - accuracy: 1.0000 - val_loss: 8.8554 - val_accuracy: 0.3446
Epoch 9723/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0030 - accuracy: 1.0000 - val_loss: 8.8560 - val_accuracy: 0.3448
Epoch 9724/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0030 - accuracy: 1.0000 - val_loss: 8.8565 - val_accuracy: 0.3447
Epoch 9725/10000
1/1 [==============================] - 0s 101ms/step - loss: 0.0030 - accuracy: 1.0000 - val_loss: 8.8573 - val_accuracy: 0.3447
Epoch 9726/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0030 - accuracy: 1.0000 - val_loss: 8.8581 - val_accuracy: 0.3447
Epoch 9727/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0030 - accuracy: 1.0000 - val_loss: 8.8587 - val_accuracy: 0.3447
Epoch 9728/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0030 - accuracy: 1.0000 - val_loss: 8.8594 - val_accuracy: 0.3447
Epoch 9729/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0030 - accuracy: 1.0000 - val_loss: 8.8601 - val_accuracy: 0.3447
Epoch 9730/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0030 - accuracy: 1.0000 - val_loss: 8.8609 - val_accuracy: 0.3447
Epoch 9731/10000
1/1 [==============================] - 0s 103ms/step - loss: 0.0030 - accuracy: 1.0000 - val_loss: 8.8615 - val_accuracy: 0.3447
Epoch 9732/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0030 - accuracy: 1.0000 - val_loss: 8.8621 - val_accuracy: 0.3447
Epoch 9733/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0030 - accuracy: 1.0000 - val_loss: 8.8628 - val_accuracy: 0.3447
Epoch 9734/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0030 - accuracy: 1.0000 - val_loss: 8.8632 - val_accuracy: 0.3447
Epoch 9735/10000
1/1 [==============================] - 0s 102ms/step - loss: 0.0030 - accuracy: 1.0000 - val_loss: 8.8639 - val_accuracy: 0.3447
Epoch 9736/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0030 - accuracy: 1.0000 - val_loss: 8.8647 - val_accuracy: 0.3446
Epoch 9737/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0030 - accuracy: 1.0000 - val_loss: 8.8653 - val_accuracy: 0.3446
Epoch 9738/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0029 - accuracy: 1.0000 - val_loss: 8.8660 - val_accuracy: 0.3446
Epoch 9739/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0029 - accuracy: 1.0000 - val_loss: 8.8666 - val_accuracy: 0.3446
Epoch 9740/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0029 - accuracy: 1.0000 - val_loss: 8.8672 - val_accuracy: 0.3446
Epoch 9741/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0029 - accuracy: 1.0000 - val_loss: 8.8678 - val_accuracy: 0.3445
Epoch 9742/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0029 - accuracy: 1.0000 - val_loss: 8.8684 - val_accuracy: 0.3446
Epoch 9743/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0029 - accuracy: 1.0000 - val_loss: 8.8690 - val_accuracy: 0.3446
Epoch 9744/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0029 - accuracy: 1.0000 - val_loss: 8.8697 - val_accuracy: 0.3447
Epoch 9745/10000
1/1 [==============================] - 0s 118ms/step - loss: 0.0029 - accuracy: 1.0000 - val_loss: 8.8704 - val_accuracy: 0.3447
Epoch 9746/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0029 - accuracy: 1.0000 - val_loss: 8.8712 - val_accuracy: 0.3447
Epoch 9747/10000
1/1 [==============================] - 0s 119ms/step - loss: 0.0029 - accuracy: 1.0000 - val_loss: 8.8718 - val_accuracy: 0.3447
Epoch 9748/10000
1/1 [==============================] - 0s 120ms/step - loss: 0.0029 - accuracy: 1.0000 - val_loss: 8.8724 - val_accuracy: 0.3447
Epoch 9749/10000
1/1 [==============================] - 0s 125ms/step - loss: 0.0029 - accuracy: 1.0000 - val_loss: 8.8730 - val_accuracy: 0.3448
Epoch 9750/10000
1/1 [==============================] - 0s 122ms/step - loss: 0.0029 - accuracy: 1.0000 - val_loss: 8.8736 - val_accuracy: 0.3447
Epoch 9751/10000
1/1 [==============================] - 0s 123ms/step - loss: 0.0029 - accuracy: 1.0000 - val_loss: 8.8743 - val_accuracy: 0.3447
Epoch 9752/10000
1/1 [==============================] - 0s 122ms/step - loss: 0.0029 - accuracy: 1.0000 - val_loss: 8.8750 - val_accuracy: 0.3446
Epoch 9753/10000
1/1 [==============================] - 0s 126ms/step - loss: 0.0029 - accuracy: 1.0000 - val_loss: 8.8756 - val_accuracy: 0.3445
Epoch 9754/10000
1/1 [==============================] - 0s 140ms/step - loss: 0.0029 - accuracy: 1.0000 - val_loss: 8.8762 - val_accuracy: 0.3445
Epoch 9755/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0029 - accuracy: 1.0000 - val_loss: 8.8767 - val_accuracy: 0.3446
Epoch 9756/10000
1/1 [==============================] - 0s 122ms/step - loss: 0.0029 - accuracy: 1.0000 - val_loss: 8.8774 - val_accuracy: 0.3447
Epoch 9757/10000
1/1 [==============================] - 0s 122ms/step - loss: 0.0029 - accuracy: 1.0000 - val_loss: 8.8780 - val_accuracy: 0.3447
Epoch 9758/10000
1/1 [==============================] - 0s 129ms/step - loss: 0.0029 - accuracy: 1.0000 - val_loss: 8.8787 - val_accuracy: 0.3447
Epoch 9759/10000
1/1 [==============================] - 0s 125ms/step - loss: 0.0029 - accuracy: 1.0000 - val_loss: 8.8794 - val_accuracy: 0.3446
Epoch 9760/10000
1/1 [==============================] - 0s 122ms/step - loss: 0.0029 - accuracy: 1.0000 - val_loss: 8.8802 - val_accuracy: 0.3446
Epoch 9761/10000
1/1 [==============================] - 0s 116ms/step - loss: 0.0029 - accuracy: 1.0000 - val_loss: 8.8809 - val_accuracy: 0.3446
Epoch 9762/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0029 - accuracy: 1.0000 - val_loss: 8.8815 - val_accuracy: 0.3447
Epoch 9763/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0029 - accuracy: 1.0000 - val_loss: 8.8820 - val_accuracy: 0.3445
Epoch 9764/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0029 - accuracy: 1.0000 - val_loss: 8.8825 - val_accuracy: 0.3445
Epoch 9765/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0029 - accuracy: 1.0000 - val_loss: 8.8832 - val_accuracy: 0.3447
Epoch 9766/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0029 - accuracy: 1.0000 - val_loss: 8.8838 - val_accuracy: 0.3446
Epoch 9767/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0029 - accuracy: 1.0000 - val_loss: 8.8845 - val_accuracy: 0.3446
Epoch 9768/10000
1/1 [==============================] - 0s 119ms/step - loss: 0.0029 - accuracy: 1.0000 - val_loss: 8.8853 - val_accuracy: 0.3444
Epoch 9769/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0029 - accuracy: 1.0000 - val_loss: 8.8860 - val_accuracy: 0.3445
Epoch 9770/10000
1/1 [==============================] - 0s 119ms/step - loss: 0.0029 - accuracy: 1.0000 - val_loss: 8.8868 - val_accuracy: 0.3445
Epoch 9771/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0029 - accuracy: 1.0000 - val_loss: 8.8873 - val_accuracy: 0.3446
Epoch 9772/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0029 - accuracy: 1.0000 - val_loss: 8.8879 - val_accuracy: 0.3445
Epoch 9773/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0029 - accuracy: 1.0000 - val_loss: 8.8883 - val_accuracy: 0.3445
Epoch 9774/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0029 - accuracy: 1.0000 - val_loss: 8.8888 - val_accuracy: 0.3446
Epoch 9775/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0029 - accuracy: 1.0000 - val_loss: 8.8894 - val_accuracy: 0.3445
Epoch 9776/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0029 - accuracy: 1.0000 - val_loss: 8.8900 - val_accuracy: 0.3444
Epoch 9777/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0029 - accuracy: 1.0000 - val_loss: 8.8908 - val_accuracy: 0.3446
Epoch 9778/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0029 - accuracy: 1.0000 - val_loss: 8.8915 - val_accuracy: 0.3444
Epoch 9779/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0029 - accuracy: 1.0000 - val_loss: 8.8924 - val_accuracy: 0.3444
Epoch 9780/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0029 - accuracy: 1.0000 - val_loss: 8.8932 - val_accuracy: 0.3444
Epoch 9781/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0029 - accuracy: 1.0000 - val_loss: 8.8938 - val_accuracy: 0.3445
Epoch 9782/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0029 - accuracy: 1.0000 - val_loss: 8.8945 - val_accuracy: 0.3444
Epoch 9783/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0029 - accuracy: 1.0000 - val_loss: 8.8950 - val_accuracy: 0.3445
Epoch 9784/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0028 - accuracy: 1.0000 - val_loss: 8.8955 - val_accuracy: 0.3446
Epoch 9785/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0028 - accuracy: 1.0000 - val_loss: 8.8961 - val_accuracy: 0.3444
Epoch 9786/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0028 - accuracy: 1.0000 - val_loss: 8.8968 - val_accuracy: 0.3445
Epoch 9787/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0028 - accuracy: 1.0000 - val_loss: 8.8974 - val_accuracy: 0.3444
Epoch 9788/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0028 - accuracy: 1.0000 - val_loss: 8.8981 - val_accuracy: 0.3444
Epoch 9789/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0028 - accuracy: 1.0000 - val_loss: 8.8989 - val_accuracy: 0.3444
Epoch 9790/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0028 - accuracy: 1.0000 - val_loss: 8.8995 - val_accuracy: 0.3445
Epoch 9791/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0028 - accuracy: 1.0000 - val_loss: 8.9000 - val_accuracy: 0.3444
Epoch 9792/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0028 - accuracy: 1.0000 - val_loss: 8.9006 - val_accuracy: 0.3446
Epoch 9793/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0028 - accuracy: 1.0000 - val_loss: 8.9013 - val_accuracy: 0.3445
Epoch 9794/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0028 - accuracy: 1.0000 - val_loss: 8.9020 - val_accuracy: 0.3445
Epoch 9795/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0028 - accuracy: 1.0000 - val_loss: 8.9028 - val_accuracy: 0.3445
Epoch 9796/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0028 - accuracy: 1.0000 - val_loss: 8.9036 - val_accuracy: 0.3445
Epoch 9797/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0028 - accuracy: 1.0000 - val_loss: 8.9043 - val_accuracy: 0.3445
Epoch 9798/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0028 - accuracy: 1.0000 - val_loss: 8.9050 - val_accuracy: 0.3446
Epoch 9799/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0028 - accuracy: 1.0000 - val_loss: 8.9055 - val_accuracy: 0.3446
Epoch 9800/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0028 - accuracy: 1.0000 - val_loss: 8.9060 - val_accuracy: 0.3446
Epoch 9801/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0028 - accuracy: 1.0000 - val_loss: 8.9065 - val_accuracy: 0.3445
Epoch 9802/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0028 - accuracy: 1.0000 - val_loss: 8.9072 - val_accuracy: 0.3444
Epoch 9803/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0028 - accuracy: 1.0000 - val_loss: 8.9080 - val_accuracy: 0.3445
Epoch 9804/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0028 - accuracy: 1.0000 - val_loss: 8.9087 - val_accuracy: 0.3444
Epoch 9805/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0028 - accuracy: 1.0000 - val_loss: 8.9094 - val_accuracy: 0.3444
Epoch 9806/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0028 - accuracy: 1.0000 - val_loss: 8.9100 - val_accuracy: 0.3445
Epoch 9807/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0028 - accuracy: 1.0000 - val_loss: 8.9104 - val_accuracy: 0.3445
Epoch 9808/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0028 - accuracy: 1.0000 - val_loss: 8.9109 - val_accuracy: 0.3445
Epoch 9809/10000
1/1 [==============================] - 0s 104ms/step - loss: 0.0028 - accuracy: 1.0000 - val_loss: 8.9114 - val_accuracy: 0.3445
Epoch 9810/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0028 - accuracy: 1.0000 - val_loss: 8.9120 - val_accuracy: 0.3445
Epoch 9811/10000
1/1 [==============================] - 0s 102ms/step - loss: 0.0028 - accuracy: 1.0000 - val_loss: 8.9127 - val_accuracy: 0.3445
Epoch 9812/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0028 - accuracy: 1.0000 - val_loss: 8.9136 - val_accuracy: 0.3444
Epoch 9813/10000
1/1 [==============================] - 0s 104ms/step - loss: 0.0028 - accuracy: 1.0000 - val_loss: 8.9144 - val_accuracy: 0.3444
Epoch 9814/10000
1/1 [==============================] - 0s 103ms/step - loss: 0.0028 - accuracy: 1.0000 - val_loss: 8.9150 - val_accuracy: 0.3444
Epoch 9815/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0028 - accuracy: 1.0000 - val_loss: 8.9156 - val_accuracy: 0.3444
Epoch 9816/10000
1/1 [==============================] - 0s 104ms/step - loss: 0.0028 - accuracy: 1.0000 - val_loss: 8.9161 - val_accuracy: 0.3444
Epoch 9817/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0028 - accuracy: 1.0000 - val_loss: 8.9166 - val_accuracy: 0.3445
Epoch 9818/10000
1/1 [==============================] - 0s 103ms/step - loss: 0.0028 - accuracy: 1.0000 - val_loss: 8.9173 - val_accuracy: 0.3445
Epoch 9819/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0028 - accuracy: 1.0000 - val_loss: 8.9180 - val_accuracy: 0.3445
Epoch 9820/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0028 - accuracy: 1.0000 - val_loss: 8.9189 - val_accuracy: 0.3444
Epoch 9821/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0028 - accuracy: 1.0000 - val_loss: 8.9197 - val_accuracy: 0.3445
Epoch 9822/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0028 - accuracy: 1.0000 - val_loss: 8.9204 - val_accuracy: 0.3445
Epoch 9823/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0028 - accuracy: 1.0000 - val_loss: 8.9210 - val_accuracy: 0.3445
Epoch 9824/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0028 - accuracy: 1.0000 - val_loss: 8.9215 - val_accuracy: 0.3445
Epoch 9825/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0028 - accuracy: 1.0000 - val_loss: 8.9219 - val_accuracy: 0.3445
Epoch 9826/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0028 - accuracy: 1.0000 - val_loss: 8.9224 - val_accuracy: 0.3444
Epoch 9827/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0028 - accuracy: 1.0000 - val_loss: 8.9230 - val_accuracy: 0.3444
Epoch 9828/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0028 - accuracy: 1.0000 - val_loss: 8.9237 - val_accuracy: 0.3445
Epoch 9829/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0028 - accuracy: 1.0000 - val_loss: 8.9245 - val_accuracy: 0.3444
Epoch 9830/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0028 - accuracy: 1.0000 - val_loss: 8.9252 - val_accuracy: 0.3444
Epoch 9831/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0027 - accuracy: 1.0000 - val_loss: 8.9259 - val_accuracy: 0.3444
Epoch 9832/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0027 - accuracy: 1.0000 - val_loss: 8.9265 - val_accuracy: 0.3444
Epoch 9833/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0027 - accuracy: 1.0000 - val_loss: 8.9270 - val_accuracy: 0.3444
Epoch 9834/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0027 - accuracy: 1.0000 - val_loss: 8.9276 - val_accuracy: 0.3444
Epoch 9835/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0027 - accuracy: 1.0000 - val_loss: 8.9282 - val_accuracy: 0.3444
Epoch 9836/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0027 - accuracy: 1.0000 - val_loss: 8.9289 - val_accuracy: 0.3444
Epoch 9837/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0027 - accuracy: 1.0000 - val_loss: 8.9297 - val_accuracy: 0.3445
Epoch 9838/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0027 - accuracy: 1.0000 - val_loss: 8.9304 - val_accuracy: 0.3444
Epoch 9839/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0027 - accuracy: 1.0000 - val_loss: 8.9312 - val_accuracy: 0.3443
Epoch 9840/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0027 - accuracy: 1.0000 - val_loss: 8.9318 - val_accuracy: 0.3444
Epoch 9841/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0027 - accuracy: 1.0000 - val_loss: 8.9323 - val_accuracy: 0.3444
Epoch 9842/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0027 - accuracy: 1.0000 - val_loss: 8.9327 - val_accuracy: 0.3444
Epoch 9843/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0027 - accuracy: 1.0000 - val_loss: 8.9332 - val_accuracy: 0.3444
Epoch 9844/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0027 - accuracy: 1.0000 - val_loss: 8.9338 - val_accuracy: 0.3443
Epoch 9845/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0027 - accuracy: 1.0000 - val_loss: 8.9346 - val_accuracy: 0.3444
Epoch 9846/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0027 - accuracy: 1.0000 - val_loss: 8.9353 - val_accuracy: 0.3444
Epoch 9847/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0027 - accuracy: 1.0000 - val_loss: 8.9362 - val_accuracy: 0.3443
Epoch 9848/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0027 - accuracy: 1.0000 - val_loss: 8.9368 - val_accuracy: 0.3443
Epoch 9849/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0027 - accuracy: 1.0000 - val_loss: 8.9374 - val_accuracy: 0.3444
Epoch 9850/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0027 - accuracy: 1.0000 - val_loss: 8.9380 - val_accuracy: 0.3444
Epoch 9851/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0027 - accuracy: 1.0000 - val_loss: 8.9384 - val_accuracy: 0.3442
Epoch 9852/10000
1/1 [==============================] - 0s 119ms/step - loss: 0.0027 - accuracy: 1.0000 - val_loss: 8.9391 - val_accuracy: 0.3443
Epoch 9853/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0027 - accuracy: 1.0000 - val_loss: 8.9397 - val_accuracy: 0.3443
Epoch 9854/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0027 - accuracy: 1.0000 - val_loss: 8.9405 - val_accuracy: 0.3441
Epoch 9855/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0027 - accuracy: 1.0000 - val_loss: 8.9411 - val_accuracy: 0.3444
Epoch 9856/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0027 - accuracy: 1.0000 - val_loss: 8.9418 - val_accuracy: 0.3443
Epoch 9857/10000
1/1 [==============================] - 0s 117ms/step - loss: 0.0027 - accuracy: 1.0000 - val_loss: 8.9425 - val_accuracy: 0.3443
Epoch 9858/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0027 - accuracy: 1.0000 - val_loss: 8.9430 - val_accuracy: 0.3443
Epoch 9859/10000
1/1 [==============================] - 0s 116ms/step - loss: 0.0027 - accuracy: 1.0000 - val_loss: 8.9436 - val_accuracy: 0.3442
Epoch 9860/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0027 - accuracy: 1.0000 - val_loss: 8.9443 - val_accuracy: 0.3443
Epoch 9861/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0027 - accuracy: 1.0000 - val_loss: 8.9450 - val_accuracy: 0.3442
Epoch 9862/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0027 - accuracy: 1.0000 - val_loss: 8.9458 - val_accuracy: 0.3443
Epoch 9863/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0027 - accuracy: 1.0000 - val_loss: 8.9464 - val_accuracy: 0.3441
Epoch 9864/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0027 - accuracy: 1.0000 - val_loss: 8.9469 - val_accuracy: 0.3442
Epoch 9865/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0027 - accuracy: 1.0000 - val_loss: 8.9474 - val_accuracy: 0.3443
Epoch 9866/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0027 - accuracy: 1.0000 - val_loss: 8.9479 - val_accuracy: 0.3443
Epoch 9867/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0027 - accuracy: 1.0000 - val_loss: 8.9486 - val_accuracy: 0.3443
Epoch 9868/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0027 - accuracy: 1.0000 - val_loss: 8.9493 - val_accuracy: 0.3443
Epoch 9869/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0027 - accuracy: 1.0000 - val_loss: 8.9501 - val_accuracy: 0.3442
Epoch 9870/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0027 - accuracy: 1.0000 - val_loss: 8.9510 - val_accuracy: 0.3442
Epoch 9871/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0027 - accuracy: 1.0000 - val_loss: 8.9516 - val_accuracy: 0.3442
Epoch 9872/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0027 - accuracy: 1.0000 - val_loss: 8.9522 - val_accuracy: 0.3443
Epoch 9873/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0027 - accuracy: 1.0000 - val_loss: 8.9527 - val_accuracy: 0.3442
Epoch 9874/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0027 - accuracy: 1.0000 - val_loss: 8.9532 - val_accuracy: 0.3442
Epoch 9875/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0027 - accuracy: 1.0000 - val_loss: 8.9538 - val_accuracy: 0.3441
Epoch 9876/10000
1/1 [==============================] - 0s 117ms/step - loss: 0.0027 - accuracy: 1.0000 - val_loss: 8.9544 - val_accuracy: 0.3442
Epoch 9877/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0027 - accuracy: 1.0000 - val_loss: 8.9550 - val_accuracy: 0.3443
Epoch 9878/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0027 - accuracy: 1.0000 - val_loss: 8.9556 - val_accuracy: 0.3443
Epoch 9879/10000
1/1 [==============================] - 0s 121ms/step - loss: 0.0027 - accuracy: 1.0000 - val_loss: 8.9563 - val_accuracy: 0.3444
Epoch 9880/10000
1/1 [==============================] - 0s 104ms/step - loss: 0.0026 - accuracy: 1.0000 - val_loss: 8.9570 - val_accuracy: 0.3442
Epoch 9881/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0026 - accuracy: 1.0000 - val_loss: 8.9575 - val_accuracy: 0.3443
Epoch 9882/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0026 - accuracy: 1.0000 - val_loss: 8.9582 - val_accuracy: 0.3443
Epoch 9883/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0026 - accuracy: 1.0000 - val_loss: 8.9588 - val_accuracy: 0.3441
Epoch 9884/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0026 - accuracy: 1.0000 - val_loss: 8.9597 - val_accuracy: 0.3442
Epoch 9885/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0026 - accuracy: 1.0000 - val_loss: 8.9604 - val_accuracy: 0.3441
Epoch 9886/10000
1/1 [==============================] - 0s 104ms/step - loss: 0.0026 - accuracy: 1.0000 - val_loss: 8.9611 - val_accuracy: 0.3442
Epoch 9887/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0026 - accuracy: 1.0000 - val_loss: 8.9618 - val_accuracy: 0.3442
Epoch 9888/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0026 - accuracy: 1.0000 - val_loss: 8.9624 - val_accuracy: 0.3444
Epoch 9889/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0026 - accuracy: 1.0000 - val_loss: 8.9629 - val_accuracy: 0.3443
Epoch 9890/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0026 - accuracy: 1.0000 - val_loss: 8.9635 - val_accuracy: 0.3444
Epoch 9891/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0026 - accuracy: 1.0000 - val_loss: 8.9642 - val_accuracy: 0.3445
Epoch 9892/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0026 - accuracy: 1.0000 - val_loss: 8.9649 - val_accuracy: 0.3444
Epoch 9893/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0026 - accuracy: 1.0000 - val_loss: 8.9655 - val_accuracy: 0.3444
Epoch 9894/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0026 - accuracy: 1.0000 - val_loss: 8.9662 - val_accuracy: 0.3444
Epoch 9895/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0026 - accuracy: 1.0000 - val_loss: 8.9667 - val_accuracy: 0.3444
Epoch 9896/10000
1/1 [==============================] - 0s 104ms/step - loss: 0.0026 - accuracy: 1.0000 - val_loss: 8.9672 - val_accuracy: 0.3444
Epoch 9897/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0026 - accuracy: 1.0000 - val_loss: 8.9678 - val_accuracy: 0.3444
Epoch 9898/10000
1/1 [==============================] - 0s 103ms/step - loss: 0.0026 - accuracy: 1.0000 - val_loss: 8.9683 - val_accuracy: 0.3443
Epoch 9899/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0026 - accuracy: 1.0000 - val_loss: 8.9689 - val_accuracy: 0.3444
Epoch 9900/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0026 - accuracy: 1.0000 - val_loss: 8.9695 - val_accuracy: 0.3444
Epoch 9901/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0026 - accuracy: 1.0000 - val_loss: 8.9702 - val_accuracy: 0.3445
Epoch 9902/10000
1/1 [==============================] - 0s 103ms/step - loss: 0.0026 - accuracy: 1.0000 - val_loss: 8.9708 - val_accuracy: 0.3445
Epoch 9903/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0026 - accuracy: 1.0000 - val_loss: 8.9715 - val_accuracy: 0.3444
Epoch 9904/10000
1/1 [==============================] - 0s 116ms/step - loss: 0.0026 - accuracy: 1.0000 - val_loss: 8.9720 - val_accuracy: 0.3444
Epoch 9905/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0026 - accuracy: 1.0000 - val_loss: 8.9727 - val_accuracy: 0.3443
Epoch 9906/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0026 - accuracy: 1.0000 - val_loss: 8.9733 - val_accuracy: 0.3445
Epoch 9907/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0026 - accuracy: 1.0000 - val_loss: 8.9741 - val_accuracy: 0.3443
Epoch 9908/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0026 - accuracy: 1.0000 - val_loss: 8.9749 - val_accuracy: 0.3444
Epoch 9909/10000
1/1 [==============================] - 0s 104ms/step - loss: 0.0026 - accuracy: 1.0000 - val_loss: 8.9756 - val_accuracy: 0.3442
Epoch 9910/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0026 - accuracy: 1.0000 - val_loss: 8.9761 - val_accuracy: 0.3444
Epoch 9911/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0026 - accuracy: 1.0000 - val_loss: 8.9766 - val_accuracy: 0.3443
Epoch 9912/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0026 - accuracy: 1.0000 - val_loss: 8.9771 - val_accuracy: 0.3444
Epoch 9913/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0026 - accuracy: 1.0000 - val_loss: 8.9778 - val_accuracy: 0.3443
Epoch 9914/10000
1/1 [==============================] - 0s 102ms/step - loss: 0.0026 - accuracy: 1.0000 - val_loss: 8.9784 - val_accuracy: 0.3444
Epoch 9915/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0026 - accuracy: 1.0000 - val_loss: 8.9791 - val_accuracy: 0.3443
Epoch 9916/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0026 - accuracy: 1.0000 - val_loss: 8.9799 - val_accuracy: 0.3443
Epoch 9917/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0026 - accuracy: 1.0000 - val_loss: 8.9806 - val_accuracy: 0.3444
Epoch 9918/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0026 - accuracy: 1.0000 - val_loss: 8.9812 - val_accuracy: 0.3443
Epoch 9919/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0026 - accuracy: 1.0000 - val_loss: 8.9818 - val_accuracy: 0.3442
Epoch 9920/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0026 - accuracy: 1.0000 - val_loss: 8.9825 - val_accuracy: 0.3443
Epoch 9921/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0026 - accuracy: 1.0000 - val_loss: 8.9832 - val_accuracy: 0.3442
Epoch 9922/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0026 - accuracy: 1.0000 - val_loss: 8.9838 - val_accuracy: 0.3442
Epoch 9923/10000
1/1 [==============================] - 0s 116ms/step - loss: 0.0026 - accuracy: 1.0000 - val_loss: 8.9844 - val_accuracy: 0.3443
Epoch 9924/10000
1/1 [==============================] - 0s 103ms/step - loss: 0.0026 - accuracy: 1.0000 - val_loss: 8.9850 - val_accuracy: 0.3443
Epoch 9925/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0026 - accuracy: 1.0000 - val_loss: 8.9855 - val_accuracy: 0.3442
Epoch 9926/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0026 - accuracy: 1.0000 - val_loss: 8.9859 - val_accuracy: 0.3443
Epoch 9927/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0026 - accuracy: 1.0000 - val_loss: 8.9866 - val_accuracy: 0.3442
Epoch 9928/10000
1/1 [==============================] - 0s 116ms/step - loss: 0.0026 - accuracy: 1.0000 - val_loss: 8.9873 - val_accuracy: 0.3441
Epoch 9929/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0026 - accuracy: 1.0000 - val_loss: 8.9881 - val_accuracy: 0.3441
Epoch 9930/10000
1/1 [==============================] - 0s 103ms/step - loss: 0.0026 - accuracy: 1.0000 - val_loss: 8.9889 - val_accuracy: 0.3441
Epoch 9931/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0025 - accuracy: 1.0000 - val_loss: 8.9897 - val_accuracy: 0.3442
Epoch 9932/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0025 - accuracy: 1.0000 - val_loss: 8.9902 - val_accuracy: 0.3442
Epoch 9933/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0025 - accuracy: 1.0000 - val_loss: 8.9907 - val_accuracy: 0.3442
Epoch 9934/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0025 - accuracy: 1.0000 - val_loss: 8.9912 - val_accuracy: 0.3444
Epoch 9935/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0025 - accuracy: 1.0000 - val_loss: 8.9917 - val_accuracy: 0.3442
Epoch 9936/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0025 - accuracy: 1.0000 - val_loss: 8.9924 - val_accuracy: 0.3442
Epoch 9937/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0025 - accuracy: 1.0000 - val_loss: 8.9931 - val_accuracy: 0.3440
Epoch 9938/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0025 - accuracy: 1.0000 - val_loss: 8.9939 - val_accuracy: 0.3441
Epoch 9939/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0025 - accuracy: 1.0000 - val_loss: 8.9948 - val_accuracy: 0.3443
Epoch 9940/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0025 - accuracy: 1.0000 - val_loss: 8.9955 - val_accuracy: 0.3442
Epoch 9941/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0025 - accuracy: 1.0000 - val_loss: 8.9961 - val_accuracy: 0.3443
Epoch 9942/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0025 - accuracy: 1.0000 - val_loss: 8.9965 - val_accuracy: 0.3443
Epoch 9943/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0025 - accuracy: 1.0000 - val_loss: 8.9970 - val_accuracy: 0.3443
Epoch 9944/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0025 - accuracy: 1.0000 - val_loss: 8.9974 - val_accuracy: 0.3443
Epoch 9945/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0025 - accuracy: 1.0000 - val_loss: 8.9982 - val_accuracy: 0.3443
Epoch 9946/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0025 - accuracy: 1.0000 - val_loss: 8.9988 - val_accuracy: 0.3443
Epoch 9947/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0025 - accuracy: 1.0000 - val_loss: 8.9996 - val_accuracy: 0.3441
Epoch 9948/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0025 - accuracy: 1.0000 - val_loss: 9.0004 - val_accuracy: 0.3444
Epoch 9949/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0025 - accuracy: 1.0000 - val_loss: 9.0011 - val_accuracy: 0.3442
Epoch 9950/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0025 - accuracy: 1.0000 - val_loss: 9.0015 - val_accuracy: 0.3442
Epoch 9951/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0025 - accuracy: 1.0000 - val_loss: 9.0020 - val_accuracy: 0.3442
Epoch 9952/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0025 - accuracy: 1.0000 - val_loss: 9.0025 - val_accuracy: 0.3442
Epoch 9953/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0025 - accuracy: 1.0000 - val_loss: 9.0031 - val_accuracy: 0.3442
Epoch 9954/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0025 - accuracy: 1.0000 - val_loss: 9.0038 - val_accuracy: 0.3442
Epoch 9955/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0025 - accuracy: 1.0000 - val_loss: 9.0045 - val_accuracy: 0.3441
Epoch 9956/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0025 - accuracy: 1.0000 - val_loss: 9.0051 - val_accuracy: 0.3441
Epoch 9957/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0025 - accuracy: 1.0000 - val_loss: 9.0058 - val_accuracy: 0.3442
Epoch 9958/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0025 - accuracy: 1.0000 - val_loss: 9.0064 - val_accuracy: 0.3443
Epoch 9959/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0025 - accuracy: 1.0000 - val_loss: 9.0071 - val_accuracy: 0.3442
Epoch 9960/10000
1/1 [==============================] - 0s 119ms/step - loss: 0.0025 - accuracy: 1.0000 - val_loss: 9.0076 - val_accuracy: 0.3442
Epoch 9961/10000
1/1 [==============================] - 0s 118ms/step - loss: 0.0025 - accuracy: 1.0000 - val_loss: 9.0083 - val_accuracy: 0.3442
Epoch 9962/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0025 - accuracy: 1.0000 - val_loss: 9.0090 - val_accuracy: 0.3442
Epoch 9963/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0025 - accuracy: 1.0000 - val_loss: 9.0097 - val_accuracy: 0.3442
Epoch 9964/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0025 - accuracy: 1.0000 - val_loss: 9.0105 - val_accuracy: 0.3442
Epoch 9965/10000
1/1 [==============================] - 0s 119ms/step - loss: 0.0025 - accuracy: 1.0000 - val_loss: 9.0111 - val_accuracy: 0.3442
Epoch 9966/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0025 - accuracy: 1.0000 - val_loss: 9.0117 - val_accuracy: 0.3442
Epoch 9967/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0025 - accuracy: 1.0000 - val_loss: 9.0124 - val_accuracy: 0.3442
Epoch 9968/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0025 - accuracy: 1.0000 - val_loss: 9.0130 - val_accuracy: 0.3442
Epoch 9969/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0025 - accuracy: 1.0000 - val_loss: 9.0135 - val_accuracy: 0.3442
Epoch 9970/10000
1/1 [==============================] - 0s 116ms/step - loss: 0.0025 - accuracy: 1.0000 - val_loss: 9.0141 - val_accuracy: 0.3442
Epoch 9971/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0025 - accuracy: 1.0000 - val_loss: 9.0147 - val_accuracy: 0.3442
Epoch 9972/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0025 - accuracy: 1.0000 - val_loss: 9.0152 - val_accuracy: 0.3442
Epoch 9973/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0025 - accuracy: 1.0000 - val_loss: 9.0158 - val_accuracy: 0.3442
Epoch 9974/10000
1/1 [==============================] - 0s 116ms/step - loss: 0.0025 - accuracy: 1.0000 - val_loss: 9.0164 - val_accuracy: 0.3442
Epoch 9975/10000
1/1 [==============================] - 0s 118ms/step - loss: 0.0025 - accuracy: 1.0000 - val_loss: 9.0172 - val_accuracy: 0.3442
Epoch 9976/10000
1/1 [==============================] - 0s 114ms/step - loss: 0.0025 - accuracy: 1.0000 - val_loss: 9.0180 - val_accuracy: 0.3442
Epoch 9977/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0025 - accuracy: 1.0000 - val_loss: 9.0186 - val_accuracy: 0.3442
Epoch 9978/10000
1/1 [==============================] - 0s 105ms/step - loss: 0.0025 - accuracy: 1.0000 - val_loss: 9.0191 - val_accuracy: 0.3442
Epoch 9979/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0025 - accuracy: 1.0000 - val_loss: 9.0197 - val_accuracy: 0.3442
Epoch 9980/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0025 - accuracy: 1.0000 - val_loss: 9.0202 - val_accuracy: 0.3442
Epoch 9981/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0025 - accuracy: 1.0000 - val_loss: 9.0208 - val_accuracy: 0.3442
Epoch 9982/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0025 - accuracy: 1.0000 - val_loss: 9.0215 - val_accuracy: 0.3441
Epoch 9983/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0025 - accuracy: 1.0000 - val_loss: 9.0221 - val_accuracy: 0.3442
Epoch 9984/10000
1/1 [==============================] - 0s 109ms/step - loss: 0.0024 - accuracy: 1.0000 - val_loss: 9.0229 - val_accuracy: 0.3442
Epoch 9985/10000
1/1 [==============================] - 0s 115ms/step - loss: 0.0024 - accuracy: 1.0000 - val_loss: 9.0235 - val_accuracy: 0.3442
Epoch 9986/10000
1/1 [==============================] - 0s 104ms/step - loss: 0.0024 - accuracy: 1.0000 - val_loss: 9.0239 - val_accuracy: 0.3442
Epoch 9987/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0024 - accuracy: 1.0000 - val_loss: 9.0244 - val_accuracy: 0.3441
Epoch 9988/10000
1/1 [==============================] - 0s 110ms/step - loss: 0.0024 - accuracy: 1.0000 - val_loss: 9.0249 - val_accuracy: 0.3442
Epoch 9989/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0024 - accuracy: 1.0000 - val_loss: 9.0255 - val_accuracy: 0.3441
Epoch 9990/10000
1/1 [==============================] - 0s 111ms/step - loss: 0.0024 - accuracy: 1.0000 - val_loss: 9.0262 - val_accuracy: 0.3442
Epoch 9991/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0024 - accuracy: 1.0000 - val_loss: 9.0269 - val_accuracy: 0.3442
Epoch 9992/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0024 - accuracy: 1.0000 - val_loss: 9.0276 - val_accuracy: 0.3442
Epoch 9993/10000
1/1 [==============================] - 0s 113ms/step - loss: 0.0024 - accuracy: 1.0000 - val_loss: 9.0284 - val_accuracy: 0.3442
Epoch 9994/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0024 - accuracy: 1.0000 - val_loss: 9.0292 - val_accuracy: 0.3441
Epoch 9995/10000
1/1 [==============================] - 0s 104ms/step - loss: 0.0024 - accuracy: 1.0000 - val_loss: 9.0298 - val_accuracy: 0.3442
Epoch 9996/10000
1/1 [==============================] - 0s 112ms/step - loss: 0.0024 - accuracy: 1.0000 - val_loss: 9.0305 - val_accuracy: 0.3440
Epoch 9997/10000
1/1 [==============================] - 0s 116ms/step - loss: 0.0024 - accuracy: 1.0000 - val_loss: 9.0311 - val_accuracy: 0.3441
Epoch 9998/10000
1/1 [==============================] - 0s 106ms/step - loss: 0.0024 - accuracy: 1.0000 - val_loss: 9.0318 - val_accuracy: 0.3440
Epoch 9999/10000
1/1 [==============================] - 0s 108ms/step - loss: 0.0024 - accuracy: 1.0000 - val_loss: 9.0325 - val_accuracy: 0.3441
Epoch 10000/10000
1/1 [==============================] - 0s 107ms/step - loss: 0.0024 - accuracy: 1.0000 - val_loss: 9.0332 - val_accuracy: 0.3441
In [ ]:
#write accuracies in a csv file
data = {'Epoch': list(range(1, len(history_tf.history['val_accuracy']) + 1)),
        'Train Accuracy': history_tf.history['accuracy'],
        'Test Accuracy': history_tf.history['val_accuracy']}
df = pd.DataFrame(data)

folder = '/content/gdrive/MyDrive/DLS/HW2/'
#folder = "/kaggle/working/"
csv_filename = 'transfer-learning-he-normal-q4.csv'
df.to_csv(folder + csv_filename, index=False)
In [ ]:
#plot the test accuracies
folder = '/content/gdrive/MyDrive/DLS/HW2/'
csv_filename1 = 'baseline-q4.csv'
df1 = pd.read_csv(folder + csv_filename1)
csv_filename2 = 'transfer-learning-he-normal-q4.csv'
df2 = pd.read_csv(folder + csv_filename2)

#plot the test accuracies from both DataFrames
plt.plot(df1['Epoch'], df1['Test Accuracy'], label='Baseline')
plt.plot(df2['Epoch'], df2['Test Accuracy'], label='Transfer Learning')
plt.xlabel('Epochs')
plt.ylabel('Validation Accuracy')
plt.legend()
plt.title('Cifar10 Baseline vs Transfer Learning')
plt.show()

As we can see, the self supervised features learn better as compared to baseline architecture.